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NEUROSCIENCE RESEARCH PROGRESS

THE BRAINSTEM AND BEHAVIOR

NEUROSCIENCE RESEARCH PROGRESS Additional books in this series can be found on Nova’s website under the Series tab.

Additional e-books in this series can be found on Nova’s website under the eBooks tab.

NEUROSCIENCE RESEARCH PROGRESS

THE BRAINSTEM AND BEHAVIOR

ROBERT LALONDE EDITOR

Copyright © 2017 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. We have partnered with Copyright Clearance Center to make it easy for you to obtain permissions to reuse content from this publication. Simply navigate to this publication’s page on Nova’s website and locate the “Get Permission” button below the title description. This button is linked directly to the title’s permission page on copyright.com. Alternatively, you can visit copyright.com and search by title, ISBN, or ISSN. For further questions about using the service on copyright.com, please contact: Copyright Clearance Center Phone: +1-(978) 750-8400 Fax: +1-(978) 750-4470 E-mail: [email protected].

NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

Library of Congress Cataloging-in-Publication Data ISBN:  H%RRN Library of Congress Control Number: 2017958575

Published by Nova Science Publishers, Inc. † New York

CONTENTS Preface Chapter 1

vii The Brainstem Reticular Formation and CNS Arousal D. Pfaff, A. Bubnys and I. Tabansky

1

Chapter 2

The Brainstem and Cerebral Activation Jean-Jacques Lemaire, Anna Sontheimer, Guillaume Coll, Catherine Sarret, Hachemi Nezzar, Sarah Rosenberg, Bénédicte Pontier, Jérôme Coste, Fabien Feschet, Adrien Wohrer, Emmanuel De Schlichting, Laurent Sakka and Vincent Lubrano

21

Chapter 3

Supraspinal Control of Locomotion Vladimir K. Berezovskii

41

Chapter 4

The Brainstem and Motor Coordination Robert Lalonde

85

Chapter 5

The Brainstem and Reaching-and-Grasping Claudia L. R. Gonzalez and Jason W. Flindall

105

vi Chapter 6

Chapter 7

Contents The Brainstem and Eye Movements: A Focus on Motor and Premotor Commands Olivier A. Coubard

119

The Brainstem and Oral Functions: The Trigeminal System in Head Posture Catherine Strazielle and Magali Hernandez

159

Chapter 8

The Brainstem and Hallucinations Michael Serby, Nicole Derish and David Roane

205

Chapter 9

The Brainstem and Aggression Rodrigo Narvaes and Rosa Maria Martins de Almeida

223

Chapter 10

The Brainstem, Arousal, and Memory Stanley O. King II and Cedric L. Williams

255

Chapter 11

The Brainstem and Executive Functions Robert Lalonde

291

Index

337

PREFACE Over the course of the last 40 years, overviews on the behavioral consequences of brainstem lesions or stimulation have been presented by Berntson and Micco (1976), Klemm and Vertes (1990), and Napier et al. (1991). “The brainstem and behavior” presents current analysis on the role of this brain region on arousal, emotions, and cognition. In chapter 1, Pfaff, Bubnys, and Tabansky describe the role of the reticular formation on arousal by outlining their theory on the properties and dynamics of nucleus gigantocellularis neurons in the medullary reticular formation as fundamental to arousal-related properties of the reticular formation as a whole, a concept of generalized arousal based on behavioral, statistical, genetic, and mechanistic data. In chapter 2, Lemaire et al. provide a wholistic view of brain activation, including clinical consequences of traumatic, ischemic, anoxic, hemorrhagic, and expansive lesions such as tumors or abscess. Multilayered facets of brainstem participation in motor control are presented in chapters 3 to 7. Berezovskii describes the neural correlates underlying locomotion, including functions of the central pattern generator and reticulospinal pathways along with theoretical approaches to locomotion as indicated by the neural optimal control system. I summarize the role of the brainstem on motor coordination at medullary, pontine, and mesencephalic levels based on clinical cases and animal models. Gonzalez and Flindall summarize the role of the brainstem on reaching and grasping,

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Robert Lalonde

with particular emphasis on cortico-subcortical circuits and their relation with the superior colliculus. A subchapter contains recent data in regard to the clinical manifestations of brainstem lesions on these types of movement. Coubard provides an overview on brainstem mechanisms affecting eye movements, including saccade and vergence dynamics together with models of binocular coordination. Strazielle and Hernandez handle brainstem mechanisms affecting orofacial movements, with particular emphasis on the anatomical organization of the trigeminal system and the postural control of the head and neck. The influence of the brainstem on neuropsychiatric phenomena as exemplified by visual, auditory, somatosensory, and olfactory hallucinations is provided in chapter 8 written by Serby, Derish, and Roane, whose contribution contains subsections on schizophrenia and Lewy body dementias. Recent data on the neuropsychiatric manifestations of aggression can be read in chapter 9 written by Narvaes and de Almeida, with particular emphasis on neurochemical pathways, mainly biogenic amines such as serotonin and dopamine as well as gamma-aminobutiric acid (GABA). In the final part of the book (chapters 10 and 11), the influence of the brainstem on cognition is presented by King and Williams regarding memory and myself regarding executive functions. King and Williams discusses the consequences of novelty and arousal on avoidance learning and the specific mediation by norepinephrine. I summarize the role of the brainstem on executive functions at pontine and mesencephalic levels based on clinical cases of Behçet's and Parkinson’s diseases, respectively, along with the effects of brainstem lesions in animals. Altogether, the book provides a synthesis of brainstem functions based on theoretical approaches as well as the most recent clinical and experimental data, leading us to ponder on how to fill up what we do not know. Robert Lalonde, PhD University of Rouen-Normandy Dept Psychology EA7475 76821 Mont-Saint-Aignan Cedex France Email: [email protected]

Preface

ix

VIAF ID: 102896257 http://viaf.org/viaf/102896257/#Lalonde,_Robert,_1954-

REFERENCES Berntson GG, Micco DJ. Organization of brainstem behavioral systems. Brain Res Bull 1976;1:471-83. Klemm KR, Vertes RP. Brainstem mechanisms of behavior . Hoboken: J. Wiley, 1990. Napier TC, Kalivas PW, Hanin I (eds) The basal forebrain: anatomy to function, Advances in Experimental Medicine and Biology, vol 295. Berlin: Springer, 1991.

In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 1

THE BRAINSTEM RETICULAR FORMATION AND CNS AROUSAL D. Pfaff, A. Bubnys and I. Tabansky The Rockefeller University, Laboratory of Neurobiology and Behavior, New York, New York US

ABSTRACT Here we present a new view of the brainstem reticular formation focusing on how it regulates CNS arousal. The chapter offers the concept that, underlying all the specific motivational states such as hunger, thirst, sex, fear, there lies a more fundamental behavior-activating system which we call generalized arousal (GA). GA contributes to and amplifies all motivational states. Further, a group of particularly large neurons in the medullary reticular formation, the neurons of Nucleus Giganto Cellularis (NGC), command a broad neuroanatomical domain. Their wide array of inputs, outputs, electrophysiological properties, and molecular identities clearly afford them the power to act as prime movers in elevating GA. We theorize that NGC and other reticular neurons operate using nonlinear dynamics in non-aroused states, and then pass through a physically definable phase transition upon adequate stimulation to energize well

Corresponding Author Email: [email protected].

2

D. Pfaff, A. Bubnys and I. Tabansky regulated behavior control programs. This line of thinking offers a new vocabulary for linking a global CNS function to the types of analyses usually applied to physical systems.

1. INTRODUCTION For decades, studies of brainstem physiology primarily concentrated on specific behavioral functions. Examples of this would include superior collicular controls over eye movements and vestibular controls over the muscles that support balance. This chapter takes the opposite direction: brainstem reticular regulation of the most elementary global function of the central nervous system: generalized arousal (GA), a concept introduced below. Examples of the lowest states of GA would include coma, deep anesthesia and deep sleep. The complexity and relative opacity of reticular core signaling pathways- both internal and to other neural regions- will be noted in the next section. In light of such complexity, it is most surprising, in our recent investigations, that it may be possible that, in quantitative terms, neurons in the brainstem reticular formation are performing operations, as an individual moves quickly from a low to a high state of arousal, operations that mimic well-understood deterministic physical systems.

2. RETICULAR FORMATION As a teaching device for his students at MIT, the well-known neuroanatomist Walle J. H. Nauta conceived of the reticular core of the mammalian brain as extending posteriorly from the central grey of the sacral spinal cord anteriorly to the central thalamus, the so-called intralaminar nuclei. Neuronal computation in the reticular core is thought of as regulating virtually all sensory and motor processes, directly or indirectly. At the two anterior/posterior extremes, prominent bodies of data show the importance of the neurons involved. Interneurons in the sacral

The Brainstem Reticular Formation and CNS Arousal

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spinal cord regulate pelvic functions of great emotional significance, such as sexual behaviors. Considering the anterior extreme, the central thalamus, we recall the first demonstration of brainstem stimulation affecting the electrical activity of the cerebral cortex (Dempsey and Morison, 1941), using electrodes placed in the central thalamus. Indeed, electrical stimulation of the central thalamus was able to heighten cognitive function in a severely brain-damaged patient (Schiff et al., 2008, 2013) and increase measures of generalized arousal (see below) in mice (Keenan et al., 2015; Tabansky et al., 2014; Quinkert et al., 2010, 2011, 2012). In between the rostral and caudal poles of the reticular core, other cell groups contribute to arousal (Moruzzi and Magoun, 1949; Magoun, 1958). Nucleus Giganto Cellularis (NGC) will be emphasized below, but cells at other levels of the neuraxis contribute as well. In the midbrain and pons, Saper and his colleagues have shown the ability of the peripeduncular nucleus to elevate arousal (Fuller et al., 2007; Saper et al., 2010), likely using both cholinergic and glutamatergic synapses (Benarroch, 2013). Regarding decreasing arousal, normal sleep depends on reticular neurons in the pons (Brown et al., 2012). Garcia-Rill et al., (2013) have reported that some of these pontine neurons are electrically coupled with each other in a sub-threshold, fluctuating manner, and that sensory inputs could modulate such coupling in a manner to promote cortical arousal. In terms of the basic structure of the brainstem reticular formation, the first clue lies in the name ‘reticular.’ It comes from its appearance, in transverse section, as a ‘reticule,’ a grid formed by large numbers of dendrites and axons. Learning from the premier neuroanatomists of the reticular formation, M. E. and A. B. Scheibel (1951, 1955, 1958, 1961), we know that perpendicular to the anterior-posterior axis of the brainstem, dendrites proliferate. Located in the medial medullary reticular formation, NGC neurons have exceptionally wide dendritic fields due to their socalled isodendendritic structure: the second dendritic segment is longer than the first segment that begins at the nerve cell body, the third longer than the second. During the course of development, dendrites and their spines are produced in increasing numbers and then partly resorbed (Hammer and Scheibel, 1981). Also known from the Scheibels are the long

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D. Pfaff, A. Bubnys and I. Tabansky

axonal projections anteriorly and posteriorly. The NGC cell ascending axons project to a broad swath of terminal fields: the pons, midbrain, central thalamus, hypothalamus, and basal forebrain (Jones and Yang 1985, 2003; Martin et al., 2011; Vertes and Martin, 1988). Their descending axons project to all levels of the spinal cord, bilaterally (Perreault et al., 2013; Peterson, 1979; Peterson et al., 1975). Reticulospinal axons are well known to control axial and proximal muscles, but Baker (2011) additionally reports that in the primate they regulate hand movements as well. Because of the many collaterals from these reticulospinal axons, an extremely densely interconnected reticular core makes calculations that we still do not entirely understand. Regarding one crucial set of inputs to the reticular formation, circadian sleep timing and other daily arousal rhythms depend on the outputs from the suprachiasmatic nucleus (SCN) of the hypothalamus. The links from the SCN to the reticular formation and thus to the initiation of locomotor activity likely involve several pathways. Through these multiple connections, there are links to the serotonergic and orexinergic systems. These can link, in turn, to the reticular formation. Thus, SCN can signal to the brainstem reticular formation in at least four ways. (i.) There is a diffusible signal from SCN to neural sites regulating locomotor activity (Silver et al., 1996). The precise targets of this diffusible signal remain to be identified. (ii.) There is a multi-synaptic pathway to the habenular complex that seems to be important in regulating locomotor activity (Paul et al., 2011). (iii.). There is a very extensive set of multisynaptic connections from SCN to numerous brain regions (Morin et al., 2013). (iv.) Indirect routes: SCN modulation of hormonal and feeding rhythms influences many hormones that act systemically, at many neural and peripheral loci (Pfaff et al., 2004) to affect activity levels, e.g., ghrelin (LeSauter, et al., 2009). We conceive of a system with dendrites perpendicular to the anteriorposterior axis and long axons running anteriorly and posteriorly with large numbers of collaterals as part of the ‘reticule.’ This densely interconnected reticular system can encounter and regulate all incoming and output systems of the brain (Scheibel and Scheibel, 1958). While the best-known

The Brainstem Reticular Formation and CNS Arousal

5

neurotransmitters in the brainstem reticular formation are the excitatory transmitter glutamate and the inhibitory GABA, muscarinic signaling (Yeomans, 2012) and serotonergic neurons in the raphe nuclei (Kinney et al., 2011) are also prominent. Orexin signaling maintains vigilance, especially in the case of the need to stay awake and hunt for food (De Lecea, 2013; Sinton, 2011). As mentioned above, the interior connectivity of the brainstem reticular formation is dense. Garcia et al’s (2011) phrase ‘networks within networks’ applies. In the midst of overwhelming complexity of the brainstem reticular formation, the size and salience of NGC neurons (see below) might offer hope of physiological understanding in quantitative terms.

3. THE CONCEPT OF ‘GENERALIZED CNS AROUSAL’ Every behavioral act of any animal or any human being requires initiation. In many cases that initiation depends on an easily identified specific motivational state such as hunger, thirst, fear, sex, etc. Years ago we hypothesized that underlying these specific motivational forces a deeper more fundamental force operates, and called the concept ‘generalized arousal’ (GA) (Pfaff, 2006). Does GA really exist? Four lines of evidence, summarized and referenced in Calderon et al., (2016) say that it does. 1) Behavioral. Psychologists examining personality structure detected the Arousal dimension in their examinations of human behavior. Ethologists saw that arousal levels were dictating the occurrence and intensity of instinctive animal behaviors. 2) Statistical. Principal component analyses of mouse behaviors associated with arousal always reveal on large component that, in different investigations, accounted for 29-45% of the data. That means that in the differential equation(s) that could mathematically express the operations of arousal systems there is one term, GA,

6

D. Pfaff, A. Bubnys and I. Tabansky that is important, but that there may be a large number of other terms some of which are still unnamed. 3) Genetic. One type of genetic evidence simply tells us that we know some of the genes that support GA: for example orexin/hypocretin and orexin receptors. Other genes reduce GA: for example, the mu opioid receptor.

Another type of evidence springs from the sentence: “You can’t breed for a function that does not exist.” Since we were able to breed for high and low GA (Weil et al., 2010), we have another line of genetic evidence for GA existence. 4) Mechanistic. Likewise, you cannot have mechanisms for a brain function that does not exist. While much work remains to be done, especially at the molecular and cellular level, to understand properly how GA works, a large amount of mechanistic data has been reviewed (Calderon et al., 2016; Pfaff, 2006; Pfaff et al., 2012) and attests to the very existence of GA. We have proposed (Calderon et al., 2016; Pfaff, 2006) that changes in CNS arousal may be expressed as a differential equation of the following form: �� ��

= ∑ � ,�

��

That is, changes in CNS arousal ( �� ) can be expressed as a multiterm

partial differential equation in which all of the many components can contribute to CNS arousal. Each component has a weight represented in the equation by a coefficients � , where Aj is a type of arousal. A large and important term represents GA (Ag), and for example, hunger(h), thirst (th), fear(f), anger (a) and sources presently obscure and unnamed (Ax….n) will contribute in order to account for 100% of the arousal-related data,

The Brainstem Reticular Formation and CNS Arousal

7

behavioral or neurophysiological. We note that quantitative relations among components are yet to be discovered. A mathematical methodology for showing how circadian regulation of arousal and fundamental GA processes interact has been worked out (Keenan et al., 2015).

4. NUCLEUS GIGANTOCELLULARIS (NGC) Our theory proposes that the properties and dynamics of NGC neurons in the medullary reticular formation are fundamental to the arousal-related properties of the reticular formation as a whole. NGC neurons have the neuroanatomical and electrophysiological properties to do the job. Elevating their activity elevates arousal. Damaging them decreases arousal. Some NGC neurons have bifurcating axons, ascending limbs having the capacity to contribute to cortical arousal and descending to autonomic arousal (see Figure 2.6 in Pfaff, 2006). Electrophysiologically, NGC neurons display characteristics expected of cells that dominate arousal mechanisms: they respond to stimuli in all modalities tested (Martin, 2010) and during development their ability to fire a train of spikes is closely correlated with the onset of the animal’s behavioral arousal (Liu et al., in press). Stimulating NGC neuronal activity electrically (Wu et al., 2007) or optogenetically (Calderon, Nature Neuroscience, under revision) changes the electroencephalogram from an un-activated state (low frequency, high amplitude) to an activated state (high frequency, low amplitude). Medullary reticular neurons that express the transcription factors Lhx3 or Chx10 might be particularly important in NGC’s stimulation of locomotion (Bretzner and Brownstone, 2013). Conversely, damaging NGC neurons (Zemlan et al., 1983) reduces the ability of the lesioned animal to initiate movement. Genetic contributions to NGC functional capacities are beginning to be explored (Tabansky et al., in preparation). Classically, Le Douarin’s work (Tan and Le Douarin, 1991) with quail-chick chimeras indicated that both the alar plate and the basal plate contribute neurons that migrate to form

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D. Pfaff, A. Bubnys and I. Tabansky

NGC during development. NGC neurons are firstborn on days E8 and E9 in the developing murine brain (McConnell, 1981; Perrault et al., 2015). According to Gray (2013), they likely have expressed developmental transcription factors Dbx1 and Chx10. In any case, when we sucked mRNAs from the cytoplasm of individual adult NGC neurons (Martin et al., 2011), we could find evidence of gene expression related to increasing arousal (orexin receptors) and decreasing arousal (opioid receptors). Finally, we have explored the hypothesis that these neurons may have evolved from the Mauthner cell in the medulla of teleost fish, although NGC neurons have a wider range of action far beyond the specific escape network served by Mauthner cells (Pfaff et al., 2012).

5. THEORY Put briefly, we propose that in animals or humans at very low states of arousal, NGC neurons are firing in time series that are dictated by nonlinear, chaotic equations. Their physiological state lies near a phase transition, a condition which generates data that can be fit by a power law. Operating near a phase transition adds ‘criticality,’ the ability to react rapidly, with great sensitivity and sufficient amplitude to alerting stimuli. In fact, in our generalized arousal assay, mice generate power law data (Proekt et al., 2012) in a constant, unchanging environment, indicating a behavior generator intrinsic to the brain that offers the advantage of scalefree behavior initiation, and thus a range of response capacity that could not be managed by a linear system. Power law data are consistent with our theory of a phase transition. Following this phase transition, orderly, programmatic signaling regulates coordinated motor behavior. An attractive extension of this thinking is to explore the notion that one or more of the equations that yield chaotic dynamics (Cohen, 1995) describes some of the non-linear dynamics needed for the reticular formation to produce ‘explosively’ behavioral reactions necessary for reproduction or survival. For example, the logistic equation

The Brainstem Reticular Formation and CNS Arousal

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Xn+1 = RXn(1-Xn) comes to mind. Chaotic systems feature exquisite sensitivity to starting position and small changes, as required in some environmental situations. We have posited that in order to be functionally effective, the brain, in low GA, must be poised in the vicinity of the transition to higher GA; that is, at a critical point between two states (Calderon et al., 2016). At what point might neural activity break out to occur in bursts, “neuronal avalanches”? For sudden changes in neural activity, the phenomenon of ‘scale invariance’ would be effective: small changes are suddenly replicated in self-similar larger scale increases and so forth. Suggestive of criticality, “scale invariance” describes dynamics that leap from tiny metrics across exponents to huge metrics and thus afford the opportunity to change states of the system very rapidly. Our data on spontaneous activation of behavior in an unchanging environment is the simplest case of arousal onset because it avoids the complexities added by specific behavioral tasks. In experiments reflecting intrinsic behavior generating mechanisms in the brainstem, we found power law data: self-similar temporal patterns reproduced on multiple time scales (Proekt et al., 2012). The ubiquitous scale-free dynamics is highly suggestive of critical-like behavior of the brain. In terms of NGC neuronal activity in the medullary reticular formation, we analogize that as the cells pass from low rates of chaotic firing through a phase transition to high rates of ordered activity, they act like a crystal composed of disordered molecules through the critical liquid crystal phase to a hard, tightly-organized full crystal (Pfaff and Banavar, 2007). To a brainstem reticular neuron, the advantages of the chaotic phase are in its exquisite sensitivity to tiny perturbations in the environment followed by an exponential amplification of activity. According to our theory, at least a fraction of brainstem reticular neurons, including NGC, have their dynamics poised in the vicinity of the phase transition to movement initiation. Upon stimulation from the environment or the viscera their rapid, non-linear dynamics push them into high rates of activity, thus to empower descending motor control signals to initiate movement.

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D. Pfaff, A. Bubnys and I. Tabansky

We have used mathematical statistics describing the crucial transition from low to high GA; that is, from quietude to the brain of the individual ready to activate a behavioral response (Hudson et al., 2014). It is this transition that represents an elevation of GA and generates behaviors described by power laws (Proekt et al., 2012) and results in ‘criticality’ of the CNS. This concept of “criticality” illustrates an advantage for arousal systems poised near a phase transition: it provides speed and sensitivity and facilitates the transition of the system into different brain states, especially as the brain crosses a phase transition from less aroused to more aroused states. In summary, concepts derived from applied mathematics of physical systems will now find their application in this area of neuroscience, the neurobiology of CNS arousal (Calderon et al., 2016). Power law statistics imply the ability of the system studied to generate dynamics of a self-similar type from extremely tiny dimensions in time and space up to tremendously large dimensions in time and space. This phenomenon, called scale invariance, leads to several striking consequences in physical systems. The first is universality- even though the elementary constituents of a system can vary, criticality and scale invariance emerge as the collective behavior of a many-body system with characteristics depending only on just a few essential attributes such as the dimensionality of the system and symmetries of the problem. A second consequence of scale invariance is that the dynamics of a system at criticality is characterized by a plethora of time scales- there is no single predictable time scale. Scale-free dynamics offer several fundamental advantages in the context of arousal, in particular to accomplish both the reactivity to very small stimuli and then to have the range to handle much larger stimuli as well. Scale invariance in time: as proposed, NGC neuronal activity patterns are expected to supply a much greater range of sensitivity than a linear system could offer, assuming that some kinds of feedback maintain the system near the transition from dynamically unstable trajectories. We must also consider scale invariance in space (Bassett et al., 2006). Engineer David Bassett believes that “brain functional networks demonstrate a fractal small-world architecture that supports critical dynamics and task-

The Brainstem Reticular Formation and CNS Arousal

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related spatial reconfiguration.” Another control system engineer, John Doyle, portrays the fan-in fan-out ‘bowtie’ configuration, which effectively describes the situation for NGC neurons, as providing optimal system performance (Csete and Doyle, 2004). These engineering suggestions remain to be tested.

6. PHASE TRANSITIONS A crucial component of the neuronal dynamics mentioned above is the phase transition from not-aroused to aroused. Sometimes brainstem circuits, notably those involving NGC, must change rapidly from a quiescent state to initiate a behavioral response. As mentioned, we have speculated (Pfaff and Banavar, 2007) that to accomplish this non-linear dynamics are required. Especially attractive theories would invoke chaotic dynamics which provide rapid amplification of signals and which are deterministic and are expressed by elegant equations. To exit from the chaotic phase of rapid change of state, arousal systems move through phase transitions to signal to orderly movement control systems. In order for CNS arousal systems to be poised in the vicinity of a critical point thus to manage the phase transition described, they may take advantage of self-organized criticality (SOC) thought to provide a general explanation for how natural systems self-tune to be in the vicinity of a critical point (Bak, 1996; Bak et al., 1987). That is, for GA to work in a biologically adaptive fashion, neither ultra-stability nor sheer instability is ideal. The biological need is for a system poised at the boundary between stability and instability and thus in the vicinity of criticality. The dynamic of the system drives it towards the critical point. In this sense, the observed criticality in the regulation of GA can be understood as resulting from the need for having accurate detection of environmental change, from tiny to huge stimuli, the need to cope with many widely diverse conditions, and the well-honed ability of the brain to react to external changes in an optimal way.

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7. SOME REASONS FOR SKEPTICISM There are several reasons to be skeptical of our theoretical suggestions. First, although Proekt’s (2012) power law data are consistent with the idea of arousal systems going through a phase transition, they do not prove it. Power law numbers can be produced by other physical processes as well. Second, in our discussions we sometimes pose dichotomies- aroused ‘versus’ not-aroused- but of course arousal functions are expected to be continuous and are of unknown shapes. Third, it is an attractive idea to suggest that simple, deterministic non-linear functions such as those yielded by equations for chaos actually dominate reticular formation dynamics in low arousal states. But it remains to be seen if detailed examination of behavioral or electrophysiological results reveal the operations of one or more chaotic systems. Fourth, even though we have emphasized here an attractive yet understudied nerve cell group, NGC, it is not yet understood how the ladder-like, intensely interconnected brainstem reticular formation as a whole take NGC’s outputs and turn them into biologically adaptive behavioral regulation. Is there, for example, the possibility of a fractal-like relation in which the dynamics of NGC signaling are ‘writ large’ as a portion of overall reticular output? Fifth, while we have in hand the transcriptome of a set of NGC neurons with extensive ascending projections (Tabansky et al., in preparation), we do not know yet whether the data will deepen our understanding of what we know superficially about NGC morphology and function or, instead, yield new insights into how NGC neurons could regulate CNS arousal. Finally, of course, systems passing through phase transitions are not necessarily the only ones to provide physical analogies for sudden elevations in CNS arousal. Earthquakes, volcanoes, and changes in hydrothermal activity all are studied with quantitative approaches. Friction laws, unstable sliding and viscoelastic modeling of deformation cycles all might give brainstem neurophysiologists comparisons to think about. Successful comparisons to physical processes offer two advantages: (i.) hints about mechanisms and (ii.) precise statements of the outputs to which those mechanisms must match.

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8. SUMMARY AND OUTLOOK The brainstem, through which forebrain signals must pass to facilitate and guide a wide variety of behaviors, features a heavily interconnected reticular core. Here we emphasize one set of large celled clusters, NGC, in the regulation of brain arousal. We hope that theoretically positing physical analogies to the arousal process will point toward the use of specific, quantitative predictions of behavioral and neurophysiological data either to confirm our theories or to force a new round of thinking and experimentation. It is striking that the behavioral and physiological dynamics of GA lead naturally to thinking based in physics. Scaling phenomena referred to in this review explain how GA systems in the brain could permit the animal to cross quickly the phase transition from inactive to active across a huge range of stimuli.

9. SOME OUTSTANDING QUESTIONS Despite the tremendous amount of progress in this field during the past two decades, many important questions remain to be answered. Some examples are given here. 1) Knowing that the generalized arousal GA contributes just one term in the equation intended to describe the overall state of CNS arousal (and changes therein), do we really know that the GA term is one-dimensional? Experiments with a wide variety of arousaldependent behaviors under many experimental conditions, followed by appropriate statistical analyses, will be required to answer this question. In turn, the physics of phase transitions in two dimensions has been studied successfully and might be relevant. 2) Even though NGC neurons are thought to provide the most essential and powerful facilitation of GA, how do we conceive of

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3)

4)

5)

6)

the contributions of the reticular formation at other levels of the neuraxis? Since, by some neuroanatomical ideas, ‘reticular dynamics’ extend from the spinal cord to the hypothalamus and central thalamus, there is a lot currently unexplained. We have optogenetic and electrophysiological evidence (Calderon, 2016, under revision) that not all NGC neurons make the same kinds of contributions to GA. How are the subdivisions of the NGC population to be conceived and described? We have the transcriptome of NGC neurons that project to the upper brainstem (Tabansky et al., ms in preparation). How do the molecular capacities of these neurons contribute to their physiological properties? How do the ladder-like connections inside the reticular formation contribute to behavioral dynamics. Do they have the effect of amplifying arousal-related signaling? What are the roles potentially served by recurrent ‘top-down’ signaling in the reticular core?

REFERENCES Bak, P. How Nature works: the science of self-organised criticality. New York: Copernicus Press, 1996. Bak, P; Tang, C; Wiesenfeld, K. Self-organized criticality: an explanation of the 1/f noise. Phys Rev Lett, 1987, 59, 381-4. Baker, SN. The primate reticulospinal tract, hand function and functional recovery. J Physiol, 2011, 589, 5603-12. Bassett, DS; Meyer-Lindenberg, A; Achard, S; Duke, T; Bullmore, E. Adaptive reconfiguration of fractal small-world human brain functional networks. Proc Natl Acad Sci USA, 2006, 103, 19518-23. Benarroch, EE. Pedunculopontine nucleus: functional organization and clinical implications. Neurology, 2013, 80, 1148-55. Bretzner, F; Brownstone, R. Lhx3-Chx10 reticulospinal neurons in locomotor circuits. J Neurosci, 2013, 33, 14681-92.

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Brown, R; Basheer, R; McKenna, JT; Strecker, RE; McCarley, RW. Control of sleep and wakefulness. Physiol Rev, 2012, 92, 1087–187. Calderon, DP; Kilinc, M; Maritan, A; Banavar, JR; Pfaff, D. Generalized CNS arousal: an elementary force within the vertebrate nervous system. Neurosci Biobehav Rev, 2016, 68, 167-76. Cohen, J. Unexpected dominance of high frequencies in chaotic nonlinear population models. Nature, 1995, 378, 610-12. Csete, M; Doyle, J. Bow ties, metabolism and disease. Trends Biotech, 2004, 22, 446-50. de Lecea, L. Optogenetic control of hypocretin (orexin) neurons and arousal circuits. Current Top Behav Neurosci, 2015, 25, 367-78. Dempsey, E; Morison, R. The production of rhythmically recurrent cortical potentials after localized thalamic stimulation. Am J Physiol--Legacy Content, 1941, 135, 293-300. Fuller, PM; Saper, CB; Lu, J. The pontine REM switch: past and present. J Physiol, 2007, 584, 735-41. Garcia, AJ 3rd; Zanella, S; Koch, H; Doi, A; Ramirez, JM. Networks within networks: the neuronal control of breathing. Prog Brain Res, 2011, 188, 31-50. Garcia-Rill, E; Kezunovic N; Hyde J; Simon C; Beck P; Urbano FJ. Coherence and frequency in the reticular activating system (RAS). Sleep Med Rev, 2013, 17, 227-38. Gray, PA. Transcription factors define the neuroanatomical organization of the medullary reticular formation. Front Neuroanat, 2013, 7, 7-26. Hammer, RP Jr; Lindsay, RD; Scheibel, AB. Development of the brain stem reticular core: an assessment of dendritic state and configuration in the perinatal rat. Brain Res, 1981, 227, 179-90. Hudson, AE; Calderon, DP; Pfaff, DW; Proekt, A. Recovery of consciousness is mediated by a network of discrete metastable activity state. Proc Natl Acad Sci, 2014, 111, 9283-8. Jones, BE. Arousal systems. Front Biosci, 2003, 8, s438-51. Jones, BE; Yang, X. The efferent projections from the reticular formation and the locus coeruleus studied by anterograde and retrograde axonal transport in the rat. J Comp Neurol, 1985, 242, 56-92.

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Keenan, DM; Quinkert, AW; Pfaff, DW. Stochastic modeling of mouse motor activity under deep brain stimulation: the extraction of arousal information. PLoS Computat Biol, 2015, 11(2), e1003883. Kinney, HC; Broadbelt, KG; Haynes, RL; Rognum, IJ; Paterson, DS. The serotonergic anatomy of the developing human medulla oblongata: implications for pediatric disorders of homeostasis. J Chem Neuroanat, 2011, 41, 182-99. LeSauter, J; Hoque N; Weintraub M; Pfaff DW; Silver, R. Stomach ghrelin-secreting cells as food-entrainable circadian clocks. Proc Natl Acad Sci, 2009, 106, 13582-7. Liu, X; Pfaff, D; Tabansky, I; Calderon, D; Kow, L-M. Development of nucleus gigantocellularis neurons correlated with the onset of behavioral arousal. Dev Neurosci, 2017; in press. Magoun, H. The waking brain. Springfield: Charles C. Thomas, 2nd ed, 1958. Martin, EM; Pavlides, C; Pfaff, D. Multimodal sensory responses of nucleus reticularis gigantocellularis and the responses' relation to cortical and motor activation. J Neurophysiol, 2010, 103, 2326-38. Martin, EM; Devidze, N; Shelley, DN; Westberg, L; Fontaine, C; Pfaff, D. Molecular and neuroanatomical characterization of single neurons in the mouse medullary gigantocellular reticular neurons. J Comp Neurol, 2011, 519, 2574-93. McConnell, JA. Identification of early neurons in the brainstem and spinal Cord. II. An autoradiographic study in the mouse. J Comp Neurol, 1981, 200, 273-88. Morin, LP. Neuroanatomy of the extended circadian rhythm system. Exp Neurol, 2013, 243, 4-20. Moruzzi, R; Magoun, H. Brain stem reticular formation and activation of the EEG. Electroencephal Clin Neurophysiol, 1949, 1, 455-73. Paul, MJ; Indic, P; Schwartz, WJ. A role for the habenula in the regulation of locomotor activity cycles. Eur J Neurosci, 2011, 34, 478–88. Perreault, M; Glover, JC. Glutamatergic reticulospinal neurons in the mouse: developmental origins, axon projections, and functional connectivity. Ann NY Acad Sci, 2013, 1279, 80-89.

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Peterson, BW. Reticulospinal projections to spinal motor nuclei. Annu Rev Physiol, 1979, 41, 127-40. Peterson, BW; Maunz, J; Pitts, W; Mackel, R. Patterns of projection and branching of reticulospinal neurons. Exp Brain Res, 1975, 23, 333-351. Pfaff, DW. Brain arousal and information theory. Cambridge: Harvard University Press, 2006. Pfaff, DW; Banavar, JR. A theoretical framework for CNS arousal. BioEssays, 2007, 29, 803-10. Pfaff, DW; Martin, EM; Faber, D. Origins of arousal: roles for medullary reticular neurons. Trends Neurosci, 2012, 35, 468-76. Pfaff, DW; Phillips, MI; Rubin, RT. Principles of hormone/behavior relations. San Diego: Elsevier/Academic Press, 2004. Proekt, A; Banavar, JR; Maritan, A; Pfaff, DW. Scale invariance in the dynamics of spontaneous behavior. Proc Natl Acad Sci, 2012, 109, 10564-9. Quinkert, AW; Pfaff, DW. Temporal patterns of deep brain stimulation generated with a true random number generator and the logistic equation: effects on CNS arousal in mice. Behav Brain Res, 2012, 229, 349-58. Quinkert, AW; Schiff, ND; Pfaff, DW. Temporal patterning of pulses during deep brain stimulation affects central nervous system arousal. Behav Brain Res, 2010, 214, 377-85. Quinkert, AW; Vimal, V; Weil, ZM; Reeke, GN; Schiff, ND; Banavar, JR; Pfaff, DW. Quantitative descriptions of generalized arousal, an elementary function of the vertebrate brain. Proc Natl Acad Sci USA, 2011, 108 Suppl 3, 15617-23. Saper, CB; Fuller, PM; Pedersen, NP; Lu, J; Scammell, TE. Sleep state switching. Neuron, 2010, 68, 1023-42. Scheibel, AB; Scheibel, ME. On detailed connections of the pontine and medullary reticular formation. Anat Rec, 1951, 109, 85. Scheibel, AB; Scheibel, ME. Axonal efferent patterns in the bulbar reticular formation. Anat Rec, 1955, 121, 362-3.

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Scheibel, AB; Scheibel, ME. Structural substrates for integrative patterns in the brainstem reticular core. In: H Jasper (ed) Reticular formation of the brain. Boston: Little Brown, 1958. Schiff, ND. Central thalamic contributions to arousal regulation and neurological disorders of consciousness. Ann NY Acad Sci, 2008, 1129, 105-18. Schiff, ND. Central thalamic deep brain stimulation for support of forebrain arousal regulation in the minimally conscious state. Handb Clin Neurol, 2013, 116, 295-306. Scheibel, ME; Scheibel, AB. On circuit patterns of the brain stem reticular core. Ann NY Acad Sci, 1961, 89, 857-65. Silver, R; LeSauter, J; Tresco, PA; Lehman, MN. A diffusible coupling signal from the transplanted suprachiasmatic nucleus controlling circadian locomotor rhythms. Nature, 1996, 382, 810-3. Sinton, CM. Orexin/hypocretin plays a role in the response to physiological disequilibrium. Sleep Med Rev, 2011, 15, 197-207. Tabansky, I; Quinkert, AW; Rahman, N; Muller, SZ; Lofgren, J; Rudling, J; Goodman, A; Wang, Y; Pfaff, DW. Temporally-patterned deep brain stimulation in a mouse model of multiple traumatic brain injury. Behav Brain Res, 2014, 273, 123-32. Tan, N; Le Douarin, NM. Development of the nuclei and cell migration in the medulla oblongata. Application of the quail-chick chimera system. Anat Embryol, 1991, 183, 321-43. Vertes, RP; Martin, GF. Autoradiographic analysis of ascending projections from the pontine and mesencephalic reticular formation and the median raphe nucleus in the rat. J Comp Neurol, 1988, 275, 511-38. Weil, ZM; Zhang, Y; Pfaff, DW. Impact of generalized brain arousal on sexual behavior. Proc Natl Acad Sci USA, 2010, 107, 2265-70. Wu, H; Stavarache, M; Pfaff, DW; Kow, L. Arousal of cerebral cortex electroencephalogram consequent to high-frequency stimulation of ventral medullary reticular formation. Proc Natl Acad Sci USA, 2007, 104, 18292-6.

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Yeomans, JS. Muscarinic receptors in brain stem and mesopontine cholinergic arousal functions. Handb Exp Pharmacol, 2012, 208, 24359. Zemlan, FP; Kow, LM; Pfaff, DW. Effect of interruption of bulbospinal pathways on lordosis, posture, and locomotion. Exp Neurol, 1983, 81, 177-94.

In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 2

THE BRAINSTEM AND CEREBRAL ACTIVATION Jean-Jacques Lemaire1,2,3,, Anna Sontheimer1,2,3, Guillaume Coll1,2,3, Catherine Sarret4,2,3, Hachemi Nezzar5,2,3, Sarah Rosenberg 6,2,3, Bénédicte Pontier1,2,3, Jérôme Coste1,2,3, Fabien Feschet2,3, Adrien Wohrer2,3, Emmanuel De Schlichting1,2,3, Laurent Sakka 1,7 and Vincent Lubrano 8 1

2



Service of Neurosurgery, CHU Clermont-Ferrand, France EA 7282 Image-Guided Clinical Neuroscience and Connectomics, Clermont Auvergne University, France 3 Institut Pascal UMR 6682, CNRS, Clermont Auvergne University, France 4 Service of Pediatrics, CHU Clermont-Ferrand, France 5 Service of Ophthalmology, CHU Clermont-Ferrand, France

Corresponding Author: Jean-Jacques Lemaire, Service de Neurochirurgie, CHU de ClermontFerrand, France. Email: [email protected].

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Service of Neurology, EEG laboratory, CHU Clermont-Ferrand, France 7 Laboratory of Anatomy, UFR Medicine, Clermont Auvergne University, France 8 Service of Neurosurgery, CHU Toulouse, France

ABSTRACT The upper brainstem is known to participate in brain activation, since the pioneering description of the Ascending Reticular System in the middle of twentieth century. Since the early works, the waking state and paradoxical sleep have been implicated in the same circuitry of activation. The consciousness cognitive process, which develops within a global cerebral workspace, is directly linked with the waking state, modulated by neurotransmitters, the most emblematic and historic being amino acids, such as glutamate (excitatory), gamma-aminobutyric acid (inhibitory); monoamines, such as serotonin and noradrenaline; and acetylcholine. From animal research, the main thalamic and extrathalamic pathways originating from the tegmentum, were precisely described. These two pathways are nowadays admitted in humans, supporting the cortical activation from the deep brain. The superior cholinergic thalamic pathway originates within dorsolateral tegmental nuclei, notably the pedunculopontine tegmental nucleus and the small laterodorsal tegmental nucleus, innervating the whole thalamus. The inferior, serotoninergic-noradrenergic basal-forebrain pathway, or extrathalamic, originates within the dorsal mesencephalon-pontine area, specifically the locus coeruleus and the dorsal raphe and central superior nuclei. Schematically, the thalamic and extra-thalamic pathways reach the hemispheric cortices, respectively through the thalamus and the hypothalamus. During several pathologic conditions, alterations of deep brain circuitry lead to disorders of consciousness, but the detailed mechanisms of dysfunctions are still not deciphered.

1. INTRODUCTION Human brain activation results in covert and overt activity, obviously present during the waking state, and commonly summarized as cerebral function or functions. Activation, coupling energetic metabolism and

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neuroglial activity (Sokoloff, 1979), emerges from permanent cerebral activity, triggered by stimuli across networks taking parts in several functions. The diurnal, basal, permanent activity was revealed along with metabolic exploration of the brain with 18F-fluorodeoxyglucose (18FFDG) Positron Emission Tomography (Pet-Scan), and in 2001, Raichle et al. (2001) introduced the concept of default mode of brain function. The subject, lying quietly, lets the mind wander, this resting state being qualified as non-goal directed. It is also named default mode network (DMN) and explored with functional magnetic resonance imaging (fMRI) at rest (Greicius et al., 2003). It is also known that the metabolism of several cortical areas decreases during goal-directed tasks, particularly the precuneus, the posterior cingulate cortex, the medial prefrontal cortex, and the ventral anterior cingulate cortex (Greicius et al., 2003; Raichle et al., 2001). In parallel, since the pioneering works on sleep, rapid-eyemovement (REM) or paradoxical phase, was characterized by brain activation similar to the waking state (Jouvet, 1965). The networks or circuits supporting cerebral functions are nowadays better understood, although we still master a limited number and part of such circuits, the most well-known being very likely the motor loop activated during several motor and non-motor tasks (e.g., Nambu, 2008). At the cellular-molecular level, all activated neurons trigger ionic and electric discharges and neuromodulators releases, propagating the reaction. Schematically, neuro-glial cells are under the influence of permanent stimuli coming from upstream neurons, and they generate a downstream activation when the overall input stimulation reaches a certain threshold. The kind of discharge and the nature of release compounds determine the resulting action on downstream neurons, and so on across the networks. This text-book knowledge is the backbone of all brain functions, including consciousness (Crick and Koch, 2005). In this chapter, we focus on the role of the brainstem on cerebral activation, particularly during the waking state and consciousness. As a consequence of developmental issues, ontogenic and phylogenic, the upper brainstem plays a particular role in the activation of the diencephalon and telencephalon. Indeed, the brainstem, along with the hypothalamus and central thalamic nuclei, can be assimilated as the basal, subcortical, neural correlates of primary or anoetic consciousness of vertebrates (Fabbro et al.,

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2015). Figure 1 depicts the anatomy of tegmentum and thalamus, where arise the most emblematic pathways activating the cortex. The chapter ends addressing some aspects of the pathophysiology of disorders of consciousness (DOC) covering coma, vegetative state (VS) or Unresponsive Wakefulness Syndrome (Laureys et al., 2010) and minimally conscious state (MCS), with regard to the role of lesions of subcortical structures linked with brainstem and cerebral activation.

2. CONSCIOUSNESS AND ACTIVATION OF THALAMO-CORTICAL PATHWAYS Consciousness is driven and modulated by triggers, the most obvious being sensory. There are convincing clues and evidence that it is a cognitive process within a global workspace (Baars, 1988; Dehaene et al., 1998), large scale, linking and binding distant cortices through cortical pyramidal neurons (layers II/III) and deep brain regions, with characteristic electroencephalographic (EEG) modifications, i.e., beta range (14-30 Hz) synchronization and gamma (30-100Hz) range late amplification (Dehaene and Changeux, 2011). This cognitive experience, if considered as highorder cognitive functioning (Brown, 2014), is modulated by the thalamus (Saalmann, 2014). In 1949, Moruzzi and Magoun illustrated the role of the brainstem in replacing synchronized EEG alpha slow waves by fast low voltage activity, during anesthesia and “encéphale isolé” experiments. The cortical desynchronization, rather ipsi and anterior, was caused by electric stimulation from 50 to 300 pulses/sec (higher frequency, better response) of the ascending reticular activation system (ARAS), running from the bulbar region up to the dorsal (posterior) hypothalamus and subthalamus (also named ventral thalamus). The effects were mediated at least partially by the thalamus and more precisely its diffuse projection system, intralaminar and posterior ventral nucleus. Moruzzi and Magoun reported that unilateral low frequency stimulation (7.5 pulses/sec) of the midline thalamus evoked bilateral cortical recruiting responses and contralateral thalamic responses, abolished by high frequency stimulation of ARAS.

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Only extended bilateral lesions of the thalamus blocked the cortical effects of ARAS high frequency stimulation.

Figure 1. Overview of tegmental and thalamic structures involved in brain activation (lateral left, posterior and superior, view). The right 3D anatomic objects are contoured from 4.7 Tesla MRI slices, and the left thalamus is represented by triplanar orthogonal MRI slices (sagittal, coronal and axial slices, respectively parallel, perpendicular and parallel with the anterior commissure – posterior commissure plan) centered on the central region of thalamus: epi, epithalamus; meta, metathalamus; medial, nucleus medial or dorso-medial; laminar, intralaminar region of thalamus; anterior, anterior or oral part of the thalamus; VTA, ventral tegmental area; tegmentum is transparent, green; brachium conjunctivum is transparent, beige; the central tegmental tract is transparent, yellow; the tegmental pedunculo-pontine nucleus is transparent, shiny green.

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The thalamo-cortical circuitry can be subdivided into two circuits according to the group of thalamic nuclei, specific or non-specific (Llinas et al., 2002). The specific system involves nuclei related to sensory and motor activity, and the unspecific system involves modulatory nuclei, anterior, lateral, intralaminar nuclei (central lateral, paracentral, central medial and parafascicular) and the midline thalamus (Van der Werf et al., 2002). Llinas et al. (Llinas et al., 2002) proposed that both specific and unspecific systems, respectively through ventrobasal (VB) nuclei and centrolateral (or central lateral, CL) intralaminar nucleus, enable by coincidence of activations the generation of supraliminal stimuli of cortical pyramidal neurons. More recently, the reticular thalamus, wrapping the thalamus around, has been involved in attention processing, filtering stimuli like a gateway to the cortex (McAlonan et al., 2008; Min, 2010; Pinault, 2004). In rats and monkeys the midline and intralaminar nuclei (MITN) show specific orbital and medial prefrontal connections, which separate this group from unspecific nuclei (Hsu and Price, 2007). The dorsal medial (or medial) nucleus, and the medial pulvinar nucleus, were also called association nuclei of thalamus, as they connect with so-called “association” cortical regions (see for an overview Chow and Hutt, 1953; Danos et al., 2003; Yeo et al., 2015). Vertes et al. (2015), more recently proposed an alternative classification: sensorimotor or principal or relay nuclei, limbic nuclei, and nuclei bridging the relay and limbic nuclei. The limbic nuclei consist of anterior nuclei, midline nuclei (the paraventricular, paratenial, reuniens and rhomboid nuclei), medial division of the mediodorsal nucleus (MDm) and central medial nucleus (CM) of the intralaminar complex (Vertes et al., 2015), the core being the MDm, CM, and midline nuclei. In monkeys, Jones (1998) pointed out the different roles of two kinds of thalamic cells with regard to calcium-binding properties: the matrix cells made up of calbindin neurons projecting to diffuse cortical areas within superficial layers (mainly layer I), and the core cells made up of parvalbumin neurons projecting to limited areas within middle layers (mainly layer IV). This distinction between matrix-calbindin (Matrix_Cal) and core-parvalbumin (Core_Parval) cells reshuffles the cards of the

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diffuse projection system. In the intralaminar group particularly, the centromedian-parafascicular complex (CMPf) is Core_Parval with specific cortical projections, and the CL nucleus is Matrix_Cal with diffuse projections. These data were completed in humans (Münkle et al., 2000) lightening the precise complementary distribution of Matrix_Cal and Core_Parval, in particular in the intralaminar nuclear group: the paracentral nucleus (Pc), CL, centromedian, and the Pf are mainly Matrix_Cal, whereas the CM is exclusively Core_Parval; in fact the lateral and intermediate subregions of the CMPf complex is Core_Parval. The reticular is Core_Parval, the anterior nuclei are combined and the dorsomedial is mixed. Schiff (2008) has also proposed to identify the central thalamus as a key player in arousal and disorders of consciousness. This central thalamus covers a quite large area and should be made up of anterior and posterior intralaminar nuclei and the paralaminar portions of related thalamic association nuclei-median dorsalis, ventral anterior, ventral lateral, and inferior pulvinar. A particular role of the centrolateral intralaminar nucleus was highlighted from works of Steriade (Steriade, 1981; Steriade et al., 1993) in cats with a 40 Hz rhythm of spike-bursts during wakefulness and REM sleep. Figure 2 and the Table 1 summarize the functional organizations of thalamic nuclei.

3. THE RETICULAR NUCLEI OF BRAINSTEM INVOLVED IN AROUSAL AND CONSCIOUSNESS The reticular formation, or substance of the brainstem where the ARAS was historically described, can be integrated within an Ascending Arousal System connecting the cerebrum through dorsal and ventral branching (Nieuwenhuys et al., 2008).

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Figure 2. Thalamic nuclei. Topography of thalamic nuclei (superior, posterior and lateral view of the left thalamus; coronal (left), sagittal (right) and axial (bottom) slices of the thalamus): AL, nucleus anterolateral; CM, nucleus centromedian; DL, dorsolateral nucleus; DM, dorsomedial nucleus; Inl, intermediolateral nucleus; La, intralaminar nuclei; Med, medial nucleus; Meta, metathalamus; Mtb, mammillothalamic bundle; Pf, parafascicular nucleus; Pu, pulvinar; Re, reticular thalamus; VCL, ventrocaudal lateral nucleus; VCM, ventrocaudal medial nucleus; VI, ventrointermediate nucleus; VO, ventro-oral nuclei.

Table 1. Thalamic nuclei related with cortical activation (see text for abbreviations) Anatomo-functional segregation

Topographic MRI anatomy

Group

Anterior (/oral)

(Mor & Magoun 1949)

Nucleus

dorsal = principal

Anteromedial

unspecific nuclei: e.g. anterior

ventral = fascicular Anterolateral

Dorsal

Dorsolateral, Dorsomedian

Intermediate

Intermediolateral

Ventrocaudal medial Medial

diffuse projection system

Parafasciculaire laminar others

Posterior (/caudal)

association nuclei

limbic nuclei: anterior

specific nuclei, or sensori-motor, or principal, or relay; e.g. ventrobasal nucleus

Jones 1998 (Macaque)

specific nuclei, or sensorimotor, or principal, or relay association nuclei

Medial

Centre median Laminar

Vertes 2015

Münkle 2000 (human)

Schiff 2008

Core_Parval

central thalamus: paralaminar region of ventral anterior nuclei

Core_Parval

central thalamus: paralaminar region of ventral lateral nuclei

unspecific nuclei : e.g. lateral

Ventrointermediate Ventrocaudal lateral

(Chow & Hutt 1953)

Core_Parval

Ventrooral

Ventral

Linas 2002; Vand Der Werf et al 2002; Hsu & Price 2007

diffuse projection system

unspecific nuclei (also MITN): centrolateral (central lateral) nucleus; paracentral nucleus; central medial; centromedian; parafascicular

Core_Parval

limbic nuclei, medial division

central thalamus: paralaminar region

Matrix_Cal limbic nuclei: central medial

Core_Parval: centromedian, parafascicular

Core_Parval: the lateral and intermediate sub regions of the CMPf complex

association nuclei: medial nuclei

Pulvinar

central thalamus: inferior region Core_Parval

Superficial lateral = reticular Superficial dorsal Superficial Superficial medial =Endymalis

Thalamus related

unspecific nuclei (also MITN): midline thalamus; reuniens, rhomboid, paraventricular and parataenial

limbic nuclei: midline nuclei; the paraventricular, paratenial, reuniens and rhomboid nuclei

Epithalamus Methalamus

Geniculate bodies

central thalamus

Matrix_Cal (rostral laminar): paracentral, central medial, parafascicular (medial)

Core_Parval

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3.1. The Superior Cholinergic Thalamic Pathway The superior cholinergic pathway uses the dorsal branching. It emerges mainly through the cholinergic dorsolateral tegmental region containing the pedunculopontine tegmental (PPtn; CH5) and nearby, the small laterodorsal tegmental nucleus (LDtn; CH6); this latter being placed in and around the locus coeruleus (Naidich et al., 2009). These nuclei are innervated by noradrenergic neurons from the A5 (nucleus paragigantocellular; near the olivary nucleus), A6 (LC, locus coeruleus), and A7 (lateral lemniscus nucleus) groups. The PPtn and LDtn innervate the entire thalamus; for example, in cats and monkeys, thalamic relay and association nuclei are innervated by cholinergic reticular nuclei of the peribrachial area (brainstem region around the brachium conjunctivum) and the laterodorsal tegmental nucleus (Steriade et al., 1988). Globally, the cholinergic nuclei of the dorsolateral part of the midbrain and rostral pons tegmentum, nucleus cuneiformis (or dorsal part of the midbrain reticular formation), PPn, LDn, project to the thalamus and notably intralaminar nuclei, midline nuclei, the reticular nucleus, and the lateral portion of MD (see Steriade et al., 1988). Although ill-defined, the nuclei of the reticular formation may reach the thalamus through two main bundles, the central tegmental tract and the longitudinal medial fascicle (Lemaire et al., 2011; Riley, 1953). The reticular and dorsomedial thalamic nuclei also receive specifically, cholinergic, as well as non-cholinergic, innervation from the substantia innominata and the nuclei of the diagonal band in cats (Steriade et al., 1987). In reality, a limited number of acetylcholine-containing neurons also project to the targeted structure of the extrathalamic pathway (Jones, 2005).

3.2. The Inferior Serotoninergic-Noradrenergic Basal Forebrain Pathway or Extrathalamic Pathway The extrathalamic pathway uses the ventral branching. Broadly it runs along the deep ventro-medio (mesio)-basal region of brain, originating

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within the dorsal mesencephalon-pontine area, specifically the LC and the dorsal raphe and central superior nuclei. The LC (A6) belongs to the noradrenergic centers. The B6-B8 (central superior, CSn) and B7 (dorsal raphe nucleus, DRn) serotoninergic (5-hydroxytryptamine; 5HT) centers belong to the median column or raphe of the reticular formation (Naidich et al., 2009; Nieuwenhuys et al., 2008). The axons follow the basal forebrain bundle, among others, reaching the hypothalamus and forebrain, hence the executive-behavioral system, and beyond the rest of the cortex.

Figure 3. Cortical activation pathways. Thalamic and extra thalamic pathways activating the hemispheric cortices: the thalamic pathway originates within the dorsolateral tegmentum, at the level of cholinergic (Ch 5 & Ch6; orange) neurons of the pedunculopontine tegmental (PPn) and laterodorsal tegmental (LD) nuclei, which are innervated by noradrenergic (A5, A6, A7 groups; blue) neurons of the locus coeruleus (LC), lateral lemniscus (LL), and paragigantocellular (PG) nuclei; the extrathalamic pathway originates in the serotoninergic (B6, B7, B8 groups;, pink) neurons of the central superior (CS) and dorsal raphe (DR) nuclei, and the noradrenergic neurons of LC (see the text for details); BnM, basal nucleus of Meynert (Ch4); Hyp, hypothalamus; Thal, thalamus.

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The LC, DRn and CSn reach the entire cortex, including the hippocampus, as well as the hypothalamus, and mesial forebrain; they also receive inputs from the hypothalamus and mesial forebrain (Naidich et al., 2009; Nieuwenhuys et al., 2008): the tuberomamillaris (histamine), preoptic (ventrolateral; GABA and galanin) and perifornical (orexin) hypothalamic nuclei; septal and accumbens nuclei (cholinergic). Figure 3 summarizes the inferior and superior pathways of arousal, waking, and consciousness.

4. FUNCTIONAL BRAIN ACTIVATION DURING SLEEP, AROUSAL, WAKING, AND CONSCIOUSNESS Consciousness, waking, arousal, and sleep phases are globally under the control of neurons in brainstem, basal forebrain, hypothalamus, and thalamus via divers transmitters and receptors (Jones, 2005; Steriade, 1993) such as acetylcholine (Ach), glutamate (Glu), serotonin (5-HT), dopamine (DA), gamma-amino butyric acid (GABA), orexin (Orx or hypocretin), noradrenaline (NA), histamine, excitatory amino acids, nitric oxide, and N-methyl-D-aspartate (NMDA) receptors. There is still no clear understanding of the overall pharmacological interactions, known since pioneering works (see e.g., during REM sleep Jones, 1991) with intricate relationships between activating cholinergic cells and inhibiting 5-HT, NA, or GABA neurons within complex neurite branching and soma vicinities. In parallel, it was inferred that complex and tangled reciprocal activation and inhibition between the thalamus, brainstem, and striatum (Llinas et al., 2002) modulate the consciousness process. Indeed, broadly, deep pyramidal neurons of cortical layer 6 exert on thalamic neurons a direct glutamatergic activation and indirect GABAergic inhibition via the reticular nucleus; the thalamus and cortex activate cortical, striatal, and pallidal neurons; GABAergic pallidal neurons and cortical inhibitory interneurons participate in local indirect feedbacks. In parallel, the inputs to the cortex, through thalamic relays, act in different manners according to

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the complexity of controls at the thalamus level, notably those exerted by cortical layer 5 cells (Sherman, 2005). Moreover, transthalamic circuits, notably with regard to glutamate pathways, support the modulation of activity between cortices, involving also subcortical structures, as in attentional processes (Sherman, 2016). The potential implication of the claustrum, or “avant-mur”, in consciousness was highlighted by Crick and Koch (2005), who suggested that this region could coordinate globally information between cortices during complex tasks. In rats, the claustrum connects reciprocally with midline, reuniens, rhomboid, paraventricular, paratenial, and centromedian nuclei of the thalamus (Vertes et al., 2015). According to Jones (2005), the pharmacodynamics of waking and REM sleep can be simplified as follows: Glu, Ach, and GABA neurons are active during the waking state and REM, whereas NA LC neurons and 5HT neurons, also active during waking, cease their activity during REM; 5HT neurons also inhibit Ach neurons (inhibiting sleep-promoting); DA, histamine, and Orx neurons stimulate brain activation, although the mechanisms are still not disentangled; GABA release within the basal forebrain, preoptic area, brainstem, and thalamus inhibits arousal; DA neurons of the substantia nigra and ventral tegmental area could participate in waking and paradoxical sleep.

5. DISORDERS OF CONSCIOUSNESS AND DEEP BRAIN LESIONS We overview here the dysfunctions of subcortical structures in the general context of lesional DOC following brain injury: essentially traumatic, ischemic, anoxic, and hemorrhagic, more rarely expansive lesions such as tumors or abscess. The implication of brainstem reticular and thalamic or extrathalamic pathways in acute stages of coma and other DOC is well documented, at least topographically, since clinical observations and autopsies in loss of consciousness related to structural or

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functional lesions of the upper brainstem at the diencephalonmesencephalic junction (see e.g., Duret, 1955; Plum and Posner, 1980). As a consequence of anatomy, lesions at this level can also impede the functionality of somatosensory pathways, which may lead to a false prognosis when measuring evoked potentials (Luauté et al., 2012). From a therapeutic perspective, all treatments at the acute stage serve to maintain life and brain functions, limiting harmful consequences of injury. The persistence of clinical symptoms in VS and MCS qualifies the clinical status as follows (“Prolonged disorders of consciousness,” 2015): (1) prolonged or continuing DOC beyond 4 weeks; (2) permanent VS, more than 6 months after a vascular cause, ischemic or hemorrhagic, or 12 months after a traumatic cause; (3) permanent MCS, after 5 years, or 3-4 years depending on the context (e.g., anoxic). Exceptionally, some patients recover later (e.g., Voss et al., 2006), making prognosis still difficult. Indeed, since the early phase following the injury, the question of continuing or stopping life-sustaining treatments is often at the core of discussions aiming for the best of the patient. Undoubtedly, better understanding of the neural correlates of DOC can help decision-making, while bearing in mind that it is just one pertinent element, besides, for example, social issues. In cases of continuing and permanent states, several invasive and noninvasive treatments have been studied, which could facilitate recovery (see Lemaire et al., 2013 for a review). Among medical treatments, only amantadine hydrochloride has proven efficacy in a placebo-controlled trial (Giacino et al., 2012), recovery being faster over a 6-week period when introduced during the early phase (from about 5 to 9 weeks following injury). This antagonist of the NMDA-type increases dopamine release and blocks reuptake as well as possessing adrenergic activity and a clinical anticholinergic effect, which altogether can lead to side effects in waking and sleep controls and other behaviors. On the other hand, zolpidem, primarily a sedative drug, can exceptionally induce spectacular recovery from MCS (Brefel-Courbon et al., 2007). Zolpidem enhances inhibitory activity of GABA transmission (Jones, 2005) by binding on GABAA receptors, specifically on the α1 subunit (Crestani et al., 2000).

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Nowadays, there is a growing body of evidence that pathophysiology of DOC relies on functional assessments in electrophysiology and imaging. Indeed, clinical observations, although critical for diagnosis, prognosis, and care protocol, are more prone to errors of interpretation, when they are rare, and when overt conscious behaviors are difficult to distinguish from unintentional reflexes. One recent hypothesis on the pathophysiology for DOC involving the brainstem focuses on the role of anterior forebrain mesocircuits (Fridman and Schiff, 2014). It must be compared to early pioneering models, more centered on the consequences of dysfunctions of thalamo-reticular activations of cortex (see e.g., Zeman, 2001). Among the cortices, it seems that the mesial cortex, prefrontal, cingulate, and precuneus are more engaged in resting state and self-awareness (Baars et al., 2003; Thibaut et al., 2012).

CONCLUSION Although we can better master the structural organization of groups of neurons involved in cortical activation, at least those of thalamic and extrathalamic pathways, the complexity of functional specificities at molecular and histological levels still impedes extensive understanding of macroscopic networks or circuits.

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In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 3

SUPRASPINAL CONTROL OF LOCOMOTION Vladimir K. Berezovskii Department of Neurobiology, Harvard Medical School, Boston, MA, US

ABSTRACT Locomotion is one of the vital functions of the organism which assures searching for food, escaping danger, and mating behavior. The brainstem plays an exceptional role in locomotor control. It participates not only in the initiation of rhythmic limb movements in vertebrates, but also maintains an appropriate muscle tone and coordination to provide propagation of the body in space. The pivotal focus of this review is the system of initiation of locomotion which includes higher motor control centers, locomotor regions of the brainstem, and central pattern generators of the spinal cord. The medioventral medullar reticular formation is the brainstem neural network which conveys the integrated inputs downstream to start locomotion. These inputs are coming from various sources, motivational signals from cerebral cortex and basal ganglia, initiating signals from the locomotor regions of the brain, and sensory information from the periphery. 

Telephone: 16174323962, Fax: 16174321639, Email: vladimir_berezovskii @hms.harvard.edu.

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Vladimir K. Berezovskii The reticulospinal relationships in different species are not the same. Spinal central pattern generators in primates and humans are highly dependent upon the downstream influence. Therefore clinical application of the experimental models obtained by studying less evolved neural networks, despite great pharmacological details that they provide, has serious restrictions. To avoid limitations of the experimental approach on higher animals the new concepts to analyze complex neural networks are needed. To achieve an ultimate goal of the locomotion study - to build the effective prosthetic devices to help patients with spinal trauma - the necessity of a theoretical approach to reinterpret the existing experimental data along with getting new ones is discussed.

1. INTRODUCTION The idea of control of body functions by the central nervous system is very old. Direct evidence that this is really happening was obtained almost two hundred years ago. The first localized function was the respiratory center in the posterior brainstem of the rabbit (Flourens, 1824; Legallois, 1812). A half century later, after the first electric stimulation of the motor cortex (Fritsch and Hitzig, 1870), the views began to emerge that the brain contains many specialized centers which are capable to turn ‘on’ and ‘off’ the corresponding functions. Since the advances in physics, especially in electricity, were so successful at the time, and applying new technologies became a routine, such views on the brain were fully justified. There is a chain of controlling centers – brain structures – which send command signals not down the wires but via neuronal axons to the peripheral tissues and organs. In the case of neuromuscular transmission, or hormone secreting cells, e.g., relatively simple “command-effect” systems, this approach remains valid until the present time. Neurologists and physiologists started the search for special areas in the brain which control more complex functions: memory, speech, locomotion. These causal relationships were grossly oversimplified, but as in any other reductionist approach, scientists did not pay too much attention to it in the hope to reveal some general principles of controlling functions through specialized neural centers.

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The hint that these centers might exist came from the observations of animal behavior after removing parts of the brain. Young rabbits after decerebration were quite capable of locomotion, “…one would say that the animal was urged forward by an internal irresistible power” (Magendi, 1845, p. 243). Hidden power was uncovered in the spinal cord which appeared to maintain locomotion even when it had been separated from the rest of the cat central nervous system (Brown, 1914). This groundbreaking discovery raised a question of how this spinal neural network, now known as the central pattern generator (CPG), is controlled by higher levels brainstem, cerebellum, basal ganglia, and cerebral cortex. Control presumes both the initiation of rhythmic movements and maintaining locomotion while regulating its speed, adapting it to terrain, etc. The primary purpose of this review is the initiation of locomotion, while other aspects of it will be covered in much less detail. Electrical stimulation of different parts of the brain, first the hypothalamus (Grossman, 1958; Waller, 1940) and then the midbrain (Shik et al., 1966) elicited locomotor movements in cat. These areas were named “locomotor,” presuming their specific command role over the performed function. Traditional neurophysiological techniques, stimulation, registration of single unit activity, and ablation, were used to study them. It was clear that understanding of these regions “…are physiological and not anatomical concepts, in that the movements observed could be due to activation of cell bodies near the electrodes or of axons originating elsewhere and traversing the stimulus site” (Eidelberg et al., 1981). Lack of appropriate morphological methods at that time did not permit to address the question of why these particular areas, but not the neighboring brain structures, are locomotor. Structure and connections of locomotor areas became a focus of attention in the mid-80s (Baev et al., 1985; Berezovskii et al., 1984, 1986; Garcia-Rill et al., 1983 b, c; Steeves and Jordan, 1984). These data are of our special interest; therefore they will be covered in detail later. Recent new technologies applied in neurobiology – optogenetics, transgenic techniques, new transsynaptic tracers, imaging – might bring the problem of the supraspinal control of locomotion to a new level. Studying

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locomotion in lower vertebrates and in mathematical models are extremely important, but they should not overshadow the ultimate goal of biomedical research of motor control - to reveal the mechanisms of initiation of locomotion in humans, and to help patients with spinal trauma.

2. INITIATION OF LOCOMOTION 2.1. Central Pattern Generator CPG is a general term to call neural networks that control the rhythmic output of the motor system. CPGs can be found in the spinal cord and in the brainstem. There are CPGs for locomotion, scratching, swimming, breathing, chewing etc. In this review the main attention will be paid to locomotion. The pharmacological approach to CPG in jawless fish lamprey has revealed that fine tuning of the networks by serotonin, dopamine and gamma-aminobutyric acid (GABA) systems involves a modulation of calcium dependent potassium channels, high and low threshold voltageactivated calcium channels and presynaptic inhibitory mechanisms (Grillner et al., 1995). In addition to the network generating swimming rhythms in lamprey spinal cord, there is also a network providing slow reciprocal alternations between dorsal and ventral parts of the myotome (Aoki et al., 2001). Moreover, the burst generator on each side may comprise at least two coupled burst generators for controlling motoneurons innervating dorsal and ventral body muscles (Buchanan, 2011). A computational model of the lamprey CPG showed that the simulated spinal network consisting of populations of excitatory and inhibitory neurons can clearly generate a replica of the biological motor pattern with a constant phase lag. Variability in response properties within each neuronal population assures a constant phase delay along the cord for different speeds of locomotion (Kozlov et al., 2009). In mice, cholinergic interneurons regulate the excitability of motoneurons during locomotion: activation of the m2 receptor leads to an

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increased excitability of motoneurons via a reduction in amplitude of the after hyperpolarization (Miles et al., 2007). Core excitatory push – inhibitory pull arrangements has been long considered to operate through each motor cycle (Grillner and Jessell, 2009). However, there are experimental data that are at odds with the widespread views. Thus, studying of motor activity in turtle spinal cord during induction of the scratch reflex revealed that coincident, rather than sequential phases of excitation and inhibition underline the rhythm: balanced excitation and inhibition and irregular firing are fundamental motifs in certain spinal network functions (Berg et al., 2007). The optogenetic approach has shown that activation of set of GABAergic neurons in the larval zebrafish elicits a prominent facilitatory influence on the locomotor network (Wyart et al., 2009). Another observation states that attenuation of glutamatergic transmission in mouse spinal interneurons through the inactivation of the gene that encodes the synaptic vesicular glutamate transporter (Vglut2) fails to disrupt fictive locomotion while respiratory pattern has been affected (Wallen-Mackenzie et al., 2006). An explanation to this might be a parallel transmitter signaling. Indeed, in mice spinal cord motoneurons corelease of glutamate and acetylcholine has been found (Nishimaru et al., 2005). Parallel transmitter signaling (GABA and acetylcholine) also exists in other divisions of the nervous system (Saunders et al., 2015). Corelease of two different neurotransmitters – against what was postulated long ago by the Dale principle (Dale, 1935) – might be a serious obstacle on the way to analyze physiological properties of neural networks using pharmacological methods. For future prospects, studies of motor control in mice offer the potential for describing the genetic manipulation of spinal interneuron network function (Hinckley et al., 2015). A molecular signature of a particular type of CPG interneurons has been shown in mice (Lanuza et al., 2004). There are changes in local circuitry and locomotor pattern after genetically programmed manipulations of interneuron sets. Matching this expanded molecular diversity to defined physiologically neuronal subtypes

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and their connections might help to reveal new principles of spinal network organization (Grillner and Jessell, 2009). For higher animals, especially for humans, complex activation patterns demand considerably greater flexibility than flexor-extensor coordination. Gigantic efforts for the past forty years to uncover the structure and function of the CPG in cat have been summarized in recent reviews (Brownstone and Bui, 2010; Jankowska, 2008). Elementary spinal interneuronal networks which can be rather simple (one or two interneurons in series between input neurons and motoneurons), are interconnected and incorporated into more complex networks as their building blocks. The precise localization of spinal interneurons involved in performing stepping behavior in cat - literally the CPG - was revealed by the c-fos immunohistochemical method. Comparative analysis after real walking versus fictive locomotion have shown that premotor interneurons in laminae VII, VIII, and X were involved in the production of locomotion, whereas interneurons in laminae III and IV were activated during locomotion due to afferent feedback from the moving limb (Dai et al., 2005). The common feature of interneuronal networks is that input from several sources is distributed to the neurons in a semi-random fashion. As for individual neurons, it may be a matter of personal preferences whether different kinds of neurons are classified as belonging to the same, or to different networks. Cells that “…appear to belong to one interneuronal population are, as a rule, intermixed with other types of neurons, are distributed over considerable lengths of spinal cord…” (Jankowska, 2008). Another group suggested that pacemakers, neurons which possess special features, in concert with emergent network properties, might consolidate the robustness of the locomotor rhythm (Brocard et al., 2010). Despite all these detailed physiological and anatomical data, it has been considered insufficient to bind known interneuronal components into testable schemes of spinal motor control (Grillner and Jessell, 2009). Another review on mammalian CPG came to a sober conclusion: after increasingly being dissected using novel tools, techniques and approaches, the CPG is still, in most parts, a ‘black box’ for which many components

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are incompletely characterized (Guertin, 2009). Such restraint inference prompts a few questions: is it true we understand the CPG and the control of its work if one reveals all of its elements and all connections between them? To what extent should we hold our traditional views on the nervous system and when is it time to reconsider them? There is another set of experiments and hypothesis on the CPG which has been, in our view, substantially overlooked. Widely known phenomena of primary afferent depolarization in spinal cord (Rudomin, 2009) has been used to study the CPG in cat (Baev and Kostyuk, 1982). It reflects the presynaptic inhibition of primary sensory afferents. During fictive locomotion, in absence of afferent input from the muscles, the CPG was still modulating input through the dorsal roots via presynaptic inhibition and performing an active selection of afferent information coming from the periphery (Baev et al., 1991b). The starting point for the developing of a new conception of the CPG was the notion that there is no single circuitry solution of construction of the generators. Many functional integration processes on dendrites are practically unobservable despite the improvement of our recording techniques. Neural circuits and networks turned out to be different in different species. CPGs for locomotion and scratching in cat significantly overlap with each other, which means that one generator can be located within another one. Authors postulated the existence within CPG of an internal model of dynamics of the controlled object, the limb, which was similar to what in neurobiological literature is known as a ‘forward’ model. The internal source of afferent information, model afferent flow, is treated by the CPG as a component of an actual afferent flow, and the abovementioned modulation of presynaptic inhibition by the CPG is a reflection of activity of the internal model (Baev and Shimansky, 1992). After limb deafferentation, the CPG relies solely on the information provided by the model. There is parity interaction between the model and actual afferent flow which is organized in such way that the network pays more attention to more intensive informational channels. In the spinal cord, presynaptic inhibition plays the role of such an ‘attention’ mechanism. Due

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to this mechanism, the more intense channel, either model or real, evokes the largest postsynaptic response when compared to typical summation. The basis for rhythm generation by the CPG after deafferentation (fictive locomotion) is not a reverberation between flexor and extensor half-centers, as was suggested by the classical view (Brown, 1914), and supported thereafter (Brocard et al., 2010; Grillner and Zangger, 1975; Guertin, 2009; Jordan and Slawinska, 2011), but rather reverberation of the activity via loops that include the internal model of the controlled object (Baev and Shimansky, 1992). This is one of the cornerstones of the principally new interpretation of CPG activity. Besides an internal model, another crucial part of the CPG had been postulated – a controller – the subsystem network that provides a governing set of commands that direct the action of the controlled object. Conceptually, CPG is regarded not as a set of specific neurons with their connections but as a special regime of activity of the neural network, e.g., CPG is a functional unity rather than an anatomical one. Development of these views led to formulating new principles of neural network organization – CPG is one of many optimal control systems in the brain (Baev, 1997, 1998, 2012). This concept substantially deviates from the mainstream approach and is still awaiting acknowledgement. Nevertheless, it would be interesting to discuss this concept later in conjunction with the initiation of locomotion.

2.2. Locomotor Regions of the Central Nervous System 2.2.1. Hypothalamic Locomotor Region The hypothalamic locomotor region (HLR) has been known as an area in posterior and lateral hypothalamus whose activation elicits locomotion in anesthetized and decorticated (Grossman, 1958; Orlovsky, 1969; Waller, 1940,) or freely moving awake cat (Mori, 1989). HLR is also described in monkey (Eidelberg et al., 1981). In lamprey, the ventral thalamus might be considered as an analog of the HLR in higher vertebrates, since its

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stimulation induced rhythmic firing of reticulospinal neurons and produced rhythmic burst activity in spinal ventral roots (El Manira et al., 1997). The HLR was stimulated to elicit walking for a study of its connections with the midbrain (Mel’nikova, 1977) and lower brainstem (Orlovsky, 1970) using electrophysiological methods. Calling this region ‘subthalamic’ often causes confusion because one of basal ganglia structures, the subthalamic nucleus, residing in close proximity, is not a part of the HLR. Instead, the subthalamic nucleus is a part of the indirect pathway in cortico-striato-thalamo-cotrical loops. Local lesions in the midbrain revealed that during locomotion, elicited by stimulation of the HLR in anesthetized rats, descending influences are transmitted through dorsal compartments of the ventral tegmental area (Sinnamon et al., 1984). On the other hand, dorsal areas of the midbrain do not participate in conveying descending commands from the HLR (Sinnamon and Stopford, 1987). Different parts of the HLR in rats are associated with initiation of locomotion in various behavioral circumstances (Sinnamon, 1993). Extensive study of structure and connections of the functionally identified HLR in cat was performed in our laboratory in the 80s. We defined the HLR as a functional union of parts of different structures: the posterolateral hypothalamus, zona innominata, and the nuclei of Forel’s fields (Baev et al., 1985). The total number of HLR neurons could be rounded up to forty five thousand. They do not have a clear-cut spatial orientation. The HLR also has diffusely distributed fibers travelling in a mediolateral direction which belong to other brain systems (Kebkalo and Berezovskii, 1993). The HLR of the two sides of the brain organize mutual connections. Areas 4 and 6 of the motor zone of the cortex and the entopeduncular nucleus project to the HLR (Baev et al., 1985). The majority of sources of brainstem afferent projections to the HLR were localized in the parabrachial nuclei along with some of the sensory nuclei which give rise to the ascending sensory tracts (Berezovskii et al., 1984). This area has extremely strong direct anatomical connections with the region of the locus coeruleus and the medial reticular formation of the caudal brainstem. The descending projections of HLR neurons are directed

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primarily to the same side of the brain and reach lumbar regions of the spinal cord (Bayev et al., 1988). There is only one group which studies the HLR in the awake, freely moving cat (Mori et al., 1989). The majority of studies of HLR have been performed in anesthetized animals, because decortication does not cancel out the stream of pain impulses to the thalamus. A study of artificially evoked locomotion was often hampered by the irregular spontaneous rhythmic movements of the limbs. This is probably the reason why HLR has been studied less than other locomotor regions of the central nervous system, especially the mesencephalic one. 2.2.2. Mesencephalic Locomotor Region It can be stated without exaggeration that the mesencephalic locomotor region (MLR) is the most popular locomotor region in the brain. It is very easy to find and place an electrode, so this experimental setup has been used extensively to elicit locomotion in different species. To cover different aspects of the MLR, it is necessary to break this subchapter into three parts.

2.2.2.1. Structure of MLR Since the first reports about the MLR, the cuneiform nucleus (CNF) has been mentioned as a main part of this area in cat (Shik et al., 1967) and monkey (Eidelberg et al., 1981). The nucleus which got its name because of its shape became known as a command center for eliciting locomotion from the midbrain. Its structure and connections were not studied at that time, leaving widely opened the question of why this particular area appeared to be so effective. The morphological study of the neuronal and fiber organization of the MLR of the cat indicated that this region consists of three major cellular structures: CNF, the medial, and the lateral parabrachial nuclei, and two fiber tracts: the lateral lemniscus and the superior cerebellar peduncle (Kebkalo and Berezovskii, 1993). The approximate total number of neurons in MLR was about forty five thousand units. The neurons in parabrachial nuclei had a clearly defined orientation - they were arranged

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alongside of the thick tract of the superior cerebellar peduncle and were elongated in the dorsolateral direction. The neurons in MLR had a primarily smaller size (23-31 ) than those in HLR (28-34 ) (Kebkalo and Berezovskii, 1993). An immunocytochemical study of the early response c-fos gene in rat revealed active neurons in MLR after injections of picrotoxin into the subpallidal region to disinhibit it and to induce locomotor activity. The cell count showed that the most significant increase of c-fos positive neurons compared to control was in pedunculopontine nuclei (PPN). For the CNF, an increase was also observed but it was not statistically significant (Brudzynski and Wang, 1996). A longstanding confusion in the brain structure nomenclature finally needs to be clarified. In cat, mesencephalic nuclei alongside the superior cerebellar peduncle (brachium conjunctivum) were long ago named “parabrachial” nuclei (Berman, 1968). This atlas has been used by anatomists for years as a major source of topography and nomenclature of the brainstem nuclei in cat. In rat, the same nuclei were often called PPN. This latter term was then applied to the cat mesencephalon substituting the term “parabrachial” nuclei (Garcia-Rill et al., 1983a). At last, there is no big difference of how to name a group of cells, but discrepancies did not stop there. Referring to PPN and to parabrachial nuclei as to separate anatomical structures only adds to the confusion (Jordan, 1998). According to this paper, the location of the MLR has been shifted a bit ventral to the deep mesencephalic reticular nuclei. The initial central role of CNF in the MLR was downplayed in favor of the PPN (Garcia-Rill, 1991). By studying the effect of excitotoxic lesions of CNF in rat on spontaneous and nucleus accumbens induced locomotion, authors came to a conclusion that the CNF is very unlikely to be an anatomical substrate of the MLR (Allen et al., 1996). Moreover, they stated that neither CNF nor PPN are uniquely involved in the control of locomotion. The final suggestion of the paper (Allen et al., 1996) that …“the term MLR itself has outlived any usefulness it might once have had and that it should be abandoned” was later challenged (Jordan, 1998). We fully support the challenge. There are many questions about the size, the

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extent of MLR, the role of fibers passing through it. What is definitely out of question is the great body of experimental data confirming that stimulation of this particular area of the midbrain is very effective in eliciting locomotion. What is, and what is not the locomotor region - this is one of the major questions of the current review. Our critical attitude to locomotor regions does not go so far as to deny the existence of the MLR and its significance. Among many places in the brainstem (Figure 1, 2), stimulation of which induces locomotion, the dorsal mesencephalic region has the greatest reason to be called locomotor.

Figure 1. Myogram of the antagonistic muscles and mechanogram of the ankle joint angle of the cat hindlimb during tonic electrical stimulation of the MLR. G – gastrocnemius muscle; TA – tibialis anterior muscle; 800 - 1200 – changes in the ankle joint angle. STIM - negative monopolar square pulses of current (5 A, 0.5 ms duration) were applied with a frequency of 50 sec-1 to the spot designated by square on the schematic drawing of the midbrain P2 level. CI – inferior colliculus, BC – brachium conjunctivum, RF – reticular formation.

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Figure 2. Spatial location of treadmill locomotion-inducing sites in the cat brain. A8 – TH6 – schematic drawings of coronal sections of the brain in the rostro-caudal direction, where A designates distance in millimeters anterior, and P – posterior to the interauricular plane; C1, C5, and TH6 designate first, fifth cervical, and sixth thoracic spinal cord segments, correspondingly (Snider and Niemer, 1961, Verhaart, 1964). Red circles indicate effective sites within known locomotor regions, HLR and MLR, which are outlined by a dashed line. Green squares designate location of the non-traditional, new locomotor regions received in our experiments by tonic electrical stimulation. Green star indicates the location of an effective locomotor site in the medioventral medulla (mRF). The rest of abbreviations are: HLR - hypothalamic locomotor region, MB - mammillary body, LGN - lateral geniculate nucleus, VTA - ventral tegmental area, CP - cerebral peduncle, I – interstitial nucleus of Cajal, R - red nucleus, MR - median raphe nucleus, PAG - periaqueductal gray, CS - superior colliculus, CI - inferior colliculus, MLR - mesencephalic locomotor region, TSV - ventral spinocerebellar tract, CN - cochlear nuclei, BC - brachium conjunctivum, VN - vestibular nuclei, SN V - nucleus tractus spinalis nervi trigemini, RB - resciform body, CN - cuneate nucleus.

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2.2.2.2. Connections of MLR Keeping in mind the discrepancies in location of the MLR is relevant in analyzing its anatomical connections in the experiments with functional identification of the region. Unfortunately, there are only few such studies. First, using electrophysiological methods, a few neurons were found in the MLR that responded to electrical stimulation of the entopeduncular nucleus with a short latency (Garcia-Rill, 1983). Fewer than 10% of the cells in the caudal region of the substantia nigra were activated antidromically when the MLR was stimulated (Garcia-Rill et al., 1983c). The pioneer morphological study performed by the same group confirmed the afferent projections to the MLR from entopeduncular nucleus and substantia nigra (Garcia-Rill, 1983b). Retrogradely labeled neurons after tracer Evans Blue injections into the MLR were also found in hypothalamus and amygdala. Downstream anterograde connections of the MLR revealed by tritiated amino acid ended up in the area of Probst’s tract in the medulla. It is noteworthy, that in the abovementioned experiments, microinjection of the mixture of antero- and retrograde transporting markers was carried out first, and then, three to four days later, the identification of MLR was performed. The morphological analysis was continued only if the microinjection site coincided with the electrolytic label of the efficient point (Garcia-Rill, 1983b). In our experiments, to achieve a perfect identification of the MLR (as well as other locomotor regions), we used a double-barreled micropipette, one channel of which was used to identify the locomotor region, and another was filled with the retrograde tracer: horseradish peroxidase solution. Figure 1 shows an example of the myogram of hindlimb muscles during tonic electrical stimulation of the MLR. Along with confirming previous sources of projections to the MLR, labeled neurons were found in the ventral tegmental area, the periaqueductal gray matter, the raphe nuclei, some sensory nuclei, and in the reticular formation of the brainstem (Berezovskii et al., 1986). Discovery of the source of afferent projections to the MLR and HLR in nuclei which give rise to ascending sensory tracts was a starting point to reconsider the role of fibers passing through these regions in the initiation

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of locomotion. This led us to a new hypothesis of how locomotor regions participate in it (Beresovskii and Bayev, 1988). Regarding efferent projections of the MLR, another autoradiographical anterograde tracing of functionally identified locomotor region, where stimulating electrode was fixed alongside the injection cannula, has shown descending projections to the ipsilateral gigantocellular and magnocellular reticular formation of the pons and medulla, dorsal tegmental reticular nucleus, and the nucleus raphe magnus (Steeves and Jordan, 1984). Explaining the differences of their results with the previous autoradiographic tracing study of more medial compartments of MLR, for which the Probst’s tract was a unique destination of their neurons (GarciaRill, 1983b), Steeves and Jordan (1984) noted that “…the classical MLR is anatomically distinct from the more medial sites in the mesencephalon which can also induce locomotion.” This adds to the question of what exactly is MLR? Injections of the retrograde tracer into functionally identified medioventral sites of medullar reticular formation confirmed projections to them from MLR (Garcia-Rill and Skinner, 1987a). We used retrograde tracing to study the efferent connections of the MLR. Observing labeled neurons in this area after injections of the tracer into a large variety of structures in the brain and spinal cord confirmed the findings obtained with anterograde tracing (Steeves and Jordan, 1984). The most prominent destination of MLR neurons was in areas of reticular formation of the midbrain and the medulla (Bayev et al., 1988). 2.2.2.3. Relationship between MLR and Reticular Formation The idea that HLR and MLR realize their influence on the CPG through the reticular formation exists since the beginning of systematic studying of locomotor regions (Shik and Orlovsky, 1976). The first electrophysiological experiments showed that reticulospinal neurons located in mediodorsal parts of the medulla oblongata respond to stimulation of the HLR and MLR with short latencies. About 70% of these neurons were activated during locomotion induced by stimulation of the MLR (Orlovsky, 1970). Later studies revealed that medioventral parts of the medulla rather than the mediodorsal receive descending MLR input

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(Garcia-Rill, 1987b). Stimulation of the MLR activates 47% of recorded neurons. About one third of studied cells in medioventral medulla were true reticulospinal neurons, which was confirmed by antidromic activation from the spinal cord. Half of them – 17% of the total population - received short-latency input from the MLR (Garcia-Rill and Skinner, 1987b). Reverse cooling of midline reticular structures can effectively block locomotion evoked by stimulation of lateral MLR sites while not significantly affecting the locomotion evoked from more medial MLR sites. In contrast, locomotion evoked by stimulation of the medial MLR is blocked by cooling of the lateral brainstem region on the same side (Shefchyk et al., 1984). Successive studies from the same laboratory, where along with reversible cooling irreversible subtotal lesions of the brainstem were used, have confirmed that the MLR does not require a pathway projecting through the lateral tegmentum of the brainstem (Noga et al., 1991). Their results indicate that the descending pathway originating from the MLR projects to the spinal cord through the medial reticular formation. The same group later provided another experimental confirmation to this view: bilateral cooling of the medial reticular formation of the medulla reversibly abolished locomotion in both hindlimbs (Noga et al., 2003). The retrograde tracing study of descending brainstem projections revealed heavy density of labeled neurons in the mesencephalic and pontine reticular formation after injections into the ventromedial medulla (Lai et al., 1999). They were found in the area which corresponds to the MLR, but the majority of labeled neurons resided presumably bilaterally in the vicinity of this region. All of the above-mentioned results in this subchapter have been obtained in cat. Lamprey also has a MLR in the form of a wellcircumscribed region located at the junction between the midbrain and hindbrain. Its relationship with the CPG was studied in detail and is summarized in a recent review (LeRay et al., 2011). Glutamatergic and cholinergic monosynaptic inputs from the MLR are responsible for excitation of reticulospinal neurons which are, in turn, activating the CPG. The MLR activates also a group of muscarinoceptive neurons in the

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brainstem that provide strong excitation on reticulospinal neurons which amplify the locomotor output (LeRay et al., 2011). It is not clear whether the same mechanism exists in cat and monkey. There is an opinion that glutamatergic and cholinergic inputs to magnocellular nucleus in cat might orchestrate different functional manifestations of this reticular structure, locomotion coordination and cardiovascular regulation, correspondingly (Lai et al., 1999). Thus, MLR projections to the medullar reticular formation are regarded as a major specific pathway of the initiation of locomotion (Brocard et al., 2010; Garcia-Rill, 1987a; Jordan, 1998, LeRay et al., 2011,). Before coming to a detailed analysis of the role of the reticular formation in the initiation of locomotion, it is worth noting that HLR and MLR are not the only known locomotor regions of the brain. 2.2.3. New Locomotor Regions For a long time, there was a hypothesis about the ponto-medullar locomotor strip, which goes through the brainstem in the rostro-caudal direction. The column of neurons in the lateral parts of pontine tegmentum and their axons got the name ‘locomotor strip’ since it was assigned the properties of transferring motor commands downstream from the MLR to CPG (Selionov and Shik, 1984). This hypothesis did not gain much support for the last three decades and now remains of historical interest. An alternative explanation of the experimental data which led to this hypothesis is needed. Why did electrical stimulation of these particular sites elicit locomotion? We address this question here along with describing other numerous non-traditional sites in the brain where electrical stimulation in our experiments initiated locomotion. From the very first experiments performed on locomotor regions, there were concerns that these areas contain many passing fibers along with the neurons (Eidelberg et al., 1981; Grossman, 1958). Of course it was found later that locomotor regions could be effectively activated pharmacologically (Garcia-Rill and Skinner, 1987a; Noga et al., 1988), which was meant to exclude the involvement of fibers from the final effect

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of stimulation. Nevertheless, electrical activation of brain areas was the first and most effective way to elicit locomotion. As was pointed out earlier, attempts to identify HLR and MLR in our laboratory to study their structure and connections using morphological tracing techniques revealed that electrical stimulation inevitably activates passing fiber systems regardless of their origin and destination. Thus, this does not constitute a random lucky discovery but rather a deliberate attempt to search for the possibility to activate the CPG by stimulating cells of origin of the fibers passing through the locomotor regions. As a matter of fact, tiny microinjection of the solution of horseradish peroxidase into low threshold (5 A) locomotion-inducing site in the lateral MLR with double barreled micropipettes resulted in retrograde cell labeling exclusively within the cochlear nuclei (Berezovskii et al., 1986). Direct electrical stimulation of the cochlear nuclei led us to the discovery of new locomotion-inducing sites in the brainstem (Baev et al., 1986). Along with the cochlear nuclei, the new locomotor sites included the ventral spinocerebellar tract which travels in pons near the superior cerebellar peduncle, and the resciform bodies, or the inferior cerebellar peduncle (Figure 2). Another set of experiments revealed effective locomotion-inducing sites in the medial midbrain – periaqueductal gray, interstitial nucleus of Cajal, nucleus raphe magnus, and even in the nucleus of the 3rd cranial nerve (Beresovskii and Bayev, 1988). Numerous attempts to study the functionally identified ‘locomotor strip’ gave us the right to suggest that we were dealing not with a special column of cells but rather with already known structures of the brainstem – the spinal trigeminal nucleus and its tract. Anatomical organization of the spinal trigeminal nucleus and its nearby tract resembles the ‘locomotor strip’ in the description of its proponents so much that is was straightforward to conclude that there is no additional anatomical structure for locomotor control in the lateral compartments of the pons and medulla; the spinal trigeminal system mimics the ‘locomotor strip’ (Baev et al., 1987). This conclusion was confirmed shortly after by the study where chemical activation of different sites of the brainstem resulted in locomotion in the decerebrate cat (Noga et al., 1988).

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In our experiments, locomotion-inducing sites were found not only in the trigeminal sensory system but also in the cuneate nucleus, inside the medial lemniscus, and on the border between dorsal horn and dorsolateral funiculus of the spinal cord. To eliminate spreading of excitation to the spinal cord via dorsal column fibers, we cut them caudally to the stimulation site (Baev et al., 1987). Finally, some effective sites were found at different levels of the spinal cord (Beresovskii, 1990). The topography of these new, non-HLR and non-MLR locomotion-inducing sites revealed in all of our experiments is plotted in Figure 2. The green squares distinguish them from the red circles which are located within the traditional HLR and MLR. There are more non-HLR and non-MLR sites effective in inducing locomotion which had been described by other investigators. The first notion was given by the pioneer of HLR studies who mentioned cerebral peduncles and areas dorsal to the red nucleus as sometimes effective in eliciting locomotion (Waller, 1940). Electrical stimulation of the proximal end of trans-sectioned medullar pyramids (Shik et al., 1968), as well as the ventrolateral funiculus of spinal cord (Yamaguchi, 1986) also induced locomotion. Among other effective sites were the nucleus centrum medianum of the thalamus (Angyan et al., 1973) and the pontine raphe nuclei (Mori et al., 1989) in the freely moving intact cat. It is noteworthy that in the anesthetized cat, stimulation of thalamic intralaminar nuclei, located rostral to the centrum medianum, inhibited spontaneous or HLRelicited locomotion (Grossman, 1958). The cerebellar stimulation of the white matter in the midline which is believed to be the axons of the fastigial nucleus was so effective and consistent that authors even coined a new term - Cerebellar Locomotor Region (Mori et al., 1999). It is remarkable that stimulation of the fastigial nucleus itself did not lead to locomotion, probably due to accompanied effects of Purkinje cell axon activation. A variety of described new locomotor regions along with already known HLR and MLR comprise a complex neural network which effectively interacts with the CPG to assure the vital function of locomotion. The medullar reticular formation sets a special place within

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this network. Despite the long history of its experimental investigation, the reticular formation remains one of the most intriguing areas of the brain.

2.3. Medullar Reticular Formation “Nowadays the term ‘reticular formation of the brain stem’ is commonly used in a very vague manner, and its connotation differs according to whether it is used by anatomists or by physiologists”. This more than half a century old quote from a classical book (Brodal, 1957, p. 2) does not seem outdated. One part of the medullar reticular formation, medioventral (mRF), serves as a crucial interface between the upper level of motor control - motor cortex, basal ganglia, HLR, MLR - and the CPG (Figure 3). As was stated in the introduction, the initiation of locomotion is the main focus of this review. Cortico-, rubro-, tecto-, and vestibulo-spinal systems play a very important role in supraspinal motor control, but only reticulospinal projections set a special place in it since they participate in both processes, the initiation of locomotion and maintaining its integrity and stability. Direct electrical or chemical activation of mRF elicits locomotion in the decerebrate cat (Garcia-Rill and Skinner, 1987a; Noga et al., 1988). Electrical stimulation of this area induced stepping movements in our experiments in the intact anesthetized cat (Berezovskii and Kebkalo, 1991). Injections of cholinergic agonists and substance P into mRF induced stepping, whereas injections of GABA blocked locomotion elicited by electrical or chemical activation of mRF or MLR (Garcia-Rill and Skinner, 1987a). Glutamic, DL-homocysteic acid and picrotoxin injections into mRF produced locomotion or lowered the current threshold for electrically induced stepping (Noga et al., 1988). It has now been widely accepted that stimulation of the MLR produces locomotion by activating reticulospinal pathways originating from the mRF (Garcia-Rill and Skinner, 1987b; Jordan, 1998). Stimulation of this area in the decerebrate cat that evoked fictive locomotion produced both excitation and inhibition of spinal motoneurons (Shefchyk and Jordan,

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1985). Another study has shown oligosynaptic excitatory postsynaptic potentials in many lumbosacral motoneurons during MLR-induced fictive locomotion (Degtyarenko et al., 1998). The average segmental latencies for some of them suggested their disynaptic origin. The involvement of the reticulospinal system in conveying signals from MLR to spinal cord was justified by cooling the ventral funiculus. This reversible procedure blocked locomotion and abolished or diminished motoneuron postsynaptic potentials (Noga et al., 2003). However, not all populations of rhythmically active motoneurons show MLR-evoked postsynaptic potentials, and it has been suggested that other excitatory lastorder interneurons without MLR input must exist to account for the depolarization of these motoneurons (Degtyarenko et al., 1998). The first candidate for this role would be the corticoreticular reticulospinal system. Corticoreticular fibers are one of the major output pathways from the premotor (area 6) and primary motor (area 4) of the cat cortex to the brainstem. They project widely and diffusely within the pontomedullary reticular formation (Kuypers, 1981; Matsuyama and Drew, 1997). Stimulation of the motor cortex excites reticulospinal neurons both mono- and poly-synaptically (Pilyavski and Gokin, 1978). Corticobulbar fibers, including the corticospinal collaterals, establish indirect corticoreticulo-spinal connections (Keizer and Kuypers, 1984). This is a multisynaptic, parallel descending system, composed of a great variety of elements. It serves to provide the optimally flexible neural substrates required for the elaboration and refinement of the wide variety of locomotor patterns used in specific, goal-directed locomotion (Matsuyama et al., 2004). The brainstem plays an important role in regulating muscle tone crucial for locomotion. Stimulation of locomotor regions in awakebehaving animals first brings the muscle tone to the appropriate level and then initiates alternating limb movements (Mori et al., 1989). A study in the decerebrate cat revealed that systematic electric stimulation of various parts of the brainstem produces different effects on muscle tone and therefore on the ability to perform locomotion. Stimulation of one region, along with tone increase, converted MLR-induced hindlimb stepping into

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coordinated quadrupedal locomotion. Activation of another site dramatically decreased an extensor tonus in the limb and suppressed the locomotion. An increase in postural tone and an activation of CPG these authors regard as non-separate phenomena (Mori et al., 1978). Another study concluded that the muscle tone inhibitory system and the locomotion executing system are under the influence of cortical excitation and basal ganglia inhibition (Takakusaki et al., 2004). By definition, the reticular formation might be considered as a ‘nonspecific’ structure since it creates a matrix where ‘specific’ nuclei (red, cranial nerves, for example) and more conspicuous tracts reside. At the same time, well-defined neuronal groups have been described within the reticular formation: pontine nuclei, gigantocellular, magnocellular reticular nuclei. Retrograde tracing techniques revealed compact groups of neurons which send descending projections to the spinal cord (Kuypers, 1981).

Figure 3. Schematic drawing of interconnections between different structures of the brain involved in the initiation of locomotion plotted on a parasagittal section of cat brain. Abbreviations: MC – motor cortex, BG – basal ganglia, HLR – hypothalamic locomotor region, MLR – mesencephalic locomotor region, mRF – medioventral medullar reticular formation, CPG – central pattern generator in spinal cord. Red arrows indicate ‘specific’ and green arrows – ‘non-specific’ inputs (detailed description is in the text).

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An important part of the descending system which initiates locomotion is the mRF. Should we consider it as a ‘specific’ or ‘non-specific’ area? Some authors regard PPN, one of the major MLR structures, as a part of the reticular activating system (Garcia-Rill et al., 2004). According to others, the CNF is a part of the mesencephalic reticular formation (Kuypers, 1981). Should we consider MLR as a ‘specific’ or ‘non-specific’ area? Division on the ‘specific’ and ‘non-specific’ physiological context has its history. In sensory physiology, the closer the observer is to the periphery, the higher the specificity, at least in vertebrates. The motor system is not traditionally divided in this way. The neuromuscular junction, for example, is very ‘specific’. We consider higher motor control centers, such as motor cortex, basal ganglia, HLR, and MLR to be ‘specific’ in the sense of goal-directed functional influence on ‘nonspecific’ lower parts of the system, mRF and CPG, which can be characterized as providers of automatic movements (Figure 3). Locomotor regions - HLR, MLR and mRF - play an important role in the initiation of locomotion but are not the only effective sites to initiate stepping. Numerous new locomotion-inducing sites described above and depicted in Figure 2 need to find their place in this system. It is possible that all these sites reach the CPG through the reticular formation. Activation of reticulospinal neurons in these cases might be different from that coming from upper motor control centers. We color-coded the two types of signals, ‘specific’ and ‘non-specific’, by red and green, correspondingly (Figure 3). It is implied that informational context makes these signals ‘specific’ or ‘non-specific’ in terms of voluntary versus automatic movements. It is important to mention that previously cited data were obtained in the cat. In other animals, Xenopus tadpole, for example, input from the trigeminal sensory nucleus could be quite ’specific’ (Buhl et al., 2012), but it remains unclear whether this is true for the animals on a higher level of the evolutionary ladder. On the other hand, the view has been expressed that “…MLR stimulation elicits locomotion by a generalized energizing action on more caudal structures” (Armstrong, 1986), which presumes

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rather ‘non-specific’ influences. The difficulty to distinguish the informational context of descending signals reflects, in our opinion, the general uncertainty in understanding the whole process of motor control. Analysis of possible effects of HLR and MLR activation, as well as the effect of stimulation of the ascending sensory fibers passing through them, along with the destination of all additional locomotor sites, resulted in the hypothesis of dual activation of mRF by many converging inputs ‘specific’ and ‘non-specific’ (Berezovskii, 1991; Beresovskii and Bayev, 1988). According to this hypothesis, there are two ways to elicit locomotion. The ‘specific’, multilevel system of initiation, encompassing the cerebral cortex, the basal ganglia, and the locomotor regions (Figure 3), works to satisfy the organism’s basic needs – movement in space, the search for food, reproductive behavior, etc. There are, however, situations when the animal needs to escape before it realizes the source of a specific danger, in cases of sudden sound, smell, or flash of light. In such instances, extraneous activation of the reticular formation is achieved by ‘nonspecific’ afferent influences. Whether the same neurons in mRF accept ‘specific’ or ‘non-specific’ inputs from different sources is a big question. Fortunately, today we have tools to test adequately this hypothesis. New tracers of a viral nature (Nassi et al., 2015; Wouterlood et al., 2014) combined with c-fos labeling as a marker for functionally active neurons during locomotion could be of tremendous help. CPG neurons which contribute to real and fictive locomotion in the cat were already accurately localized using the c-fos method, but it is not clear whether the location of neurons in the brainstem was analyzed in the same animals (Dai et al., 2005). Even if there is a separation at the input level, the output of mRF apparently is a ‘non-specific’ tonic descending stream of impulses which activates CPG. The strength and significance of this stream in animals standing on different levels of the evolutional ladder is, probably, the most important part of descending motor control. The capacity for restoring locomotor function in animals with a transected spinal cord is quite high (Barbeau and Rossignol, 1987, Rossignol, 2000), but it is inversely

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proportional to the degree of organization and specialization of the nervous system in evolutionary ranking (Eidelberg et al., 1981).

3. THEORETICAL APPROACH TO STUDY SUPRASPINAL MOTOR CONTROL As was mentioned in the beginning, a new concept of brain functions has been proposed (Baev, 1998, 2012, neurallaws.com). According to this view, the optimal control system is the key in understanding how the brain works. Historically, this concept was based on two advances – revealing the neural network computational principle and the solution of the CPG problem. The essence of the first advance is the following. Biological neural networks perform information processing that, from the mathematical standpoint, means computation. Neurocomputing has revealed a neural network computational principle and has convincingly demonstrated how multilayer networks perform approximations of functions of many variables by adjusting synaptic weights. The principle explains many nontrivial capabilities of biological neural networks: (a) the same neural network is capable of approximating different functions of many variables; (b) networks with different architectures can approximate the same functions of many variables; (c) the network computational principle explains why biological neural networks possess holographic properties – the capability to function after partial lesions. The universal solution of the CPG problem originated from studying interactions between spinal CPGs with peripheral afferent flows (Baev et al., 1991 a,b). It was shown that CPGs have internal models of their controlled objects. It follows from the control theory that only optimal control systems, that is, learning systems, are capable of building dynamic models of the behavior of their controlled objects. Several fundamental conclusions were made based on this solution: (a) CPGs, for example hindlimb locomotion and scratching, should be considered as different

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regimes of work of the same neural optimal control system (NOCS); (b) if the lowest spinal level consists of NOCSs, then higher located controlling systems should also be NOCSs capable of building internal models; (c) NOCSs are responsible for all the automatisms of the nervous system – both inborn and acquired. The new optimal control concept, which has been practically ignored by the scientific community, goes way beyond locomotion and scratching. It has been used to explain functions at the highest brain levels, symptoms of Parkinson’s disease, and analysis of the effects of deep brain stimulation (Baev, 2012; Baev et al., 2002). The following is a very sketchy description of a NOCS. Each one consists of two functional blocks – the internal model of the control object and the controller. The NOCS receives several types of signals – initiating and informational. The internal model is used in two ways – to determine the current state of the controlled object and to predict its future state. The controller uses the information about the current state of the controlled object to compute the controlling output. Both the model and the controller use various initiating signals to learn to minimize errors during their functions. One of those signals can be a mismatch between peripheral and model flows. Neural networks (NOCSs) are constantly evolving systems, which tune up the synaptic weights of their elements. The learning process for them starts some time before birth and continue throughout life; optimization is impossible without learning. According to this concept, the model and the controller can be anatomically inseparable. For instance, in the case of simple controlling systems built on pacemaker neurons, both the model and the controller are functionally built on the same neuron. In complex systems, such as cortico-basal ganglia-thalamo-cortical loops, these functional subunits can be built on partially separated networks – the basal ganglia are the major substrate for building the model. Creation of the new concept of brain functions required putting together many notions like the model, the controller , initiating and informational signals, the hierarchy, the network computational principle , learning, optimality, etc. (Baev, 2012). Without one of those notions, the whole concept does not hold together. There is no intent to produce an

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impression that some of those terms and ideas were not applied before, but they were not systematically used together for brain function analysis. The idea of an ‘action acceptor’ was formulated several decades ago (Anokhin, 1974, p. 325). The term ‘efference copy’ was introduced even earlier (von Holst and Mittelstaedt, 1950). It has been applied mainly to an internal brain signal informing the visual system of commands to move the eye. The ‘predictive brain’ hypothesis is widely known in cognitive neuroscience (Bubic et al., 2010). A ‘forward’ model conception is the necessary component to build a prediction.

Figure 4. Reinterpretation of the scheme presented on Fig 3 based on the neural optimal control concept (Baev, 1998). Color coded four levels of the hierarchy of the neural optimal control systems (NOCSs) involved in the initiation of locomotion. Each NOCS has its own controlled object, and at the same time serves as controlled object for the ‘higher’ NOCS. Arrows indicate the initiation signals. Abbreviations are the same as in Figure 3.

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A comparison in the components of schematic representations of different theoretical models reveals many similarities (for example, Figure 4 in Baev et al., 2002 and Figure 3 in Bubic et al., 2010). Nevertheless, substantial differences exist. The optimal control concept is the only one which builds a hierarchy of NOCSs; virtually the whole brain is a combination of NOCSs at different levels. A ‘lower’ NOCS serves as a controlled object for a ‘higher’ NOCS, which means that there is a model of ‘lower’ NOCS in the ‘higher’ NOCS (Figure 4). This is not what the traditional ‘forward’ model presumes. Within the framework of the new concept, special attention is also paid to a relationship between structure and function. It is impossible in this review to go through all the ramifications of the described theoretical generalization. Formulated in 1992, shaped to its current version in 1997 and 1998, and reintroduced in a recent review (Baev, 2012), this concept, in our opinion, deserves attention from the motor control community. It might not have readily complete answers to some complex questions but at least it helps to find them by designing new experimental approaches and allowing the reinterpretation of existing experimental data. Looking for ways to apply different functional models of brain activity for processing experimental data is one of the most challenging tasks for neuroscientists in the upcoming decade.

CONCLUSION Papers cited in this review provide detailed analysis of the main components of the locomotor system – the CPG itself, descending influences from brainstem and higher levels, as well as structure and connections of locomotor regions. In mammals, in contrast to invertebrates, there is probably no single major neuron or group of neurons whose lack makes the initiation of locomotion impossible. That positively speaks against the ‘specificity’ of locomotion initiation. ‘Non-specific’ neural networks contain so many discrete elements that ‘specificity’ of

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each of them is impossible to define. Perhaps the necessity of this type of definition will one day not even be relevant. The majority of described facts was obtained in the cat. There is also a substantial portion of data regarding locomotor mechanisms in a lower vertebrate – the lamprey. The claim has been made recently that “the major features of the spinal networks underlying locomotor movements in fish and other swimming vertebrates are now understood” (Grillner and El Manira, 2015, p. 247). Nevertheless, it is unclear to what extent these two sets of data are interchangeable. Despite obvious similarities between the neuronal organization of the locomotor system in the lamprey and cat – existence of CPG, locomotor regions in the brainstem, exceptional role of the reticular formation in the supraspinal control of locomotion (LeRay et al., 2011) – principles of lamprey swimming mechanisms should be applied to quadrupedal locomotion in higher vertebrates with great caution. Experimental studies in monkeys and clinical observations in humans have already confirmed this heedful assumption. After acute spinalization in macaque monkey, application of dihydroxyphenylalanine derivatives failed to elicit fictive locomotion. Chronic spinalization also failed to obtain stepping on the treadmill even after weeks and months of repeated training (Eidelberg et al., 1981). Early clinical observations were in agreement with the findings in monkey: there was no evidence of clear-cut stepping behavior in humans after anatomically verified complete spinal cord transection (Holmes, 1915, Kuhn, 1950). One explanation of these observations could be that monkeys (and probably humans) do not possess a CPG. An alternative explanation is that the CPG exists in primates but its activity is much more dependent on downstream tonic influences from the brainstem. In this case, primates, not cat or lamprey, should become the major experimental model for studying the supraspinal control of locomotion in humans. There is an indication that fictive locomotor patterns could be pharmacologically evoked in the acutely spinalized marmoset (Fedirchuk et al., 1998). More recent clinical observations proved the existence of the CPG in humans (Calancie et al., 1994, Harkema, 2008). It has been suggested that spinal circuitry in humans has the capability of generating locomotor-like activity even when

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isolated from brain control, and that externally controlled sustained electrical stimulation of the spinal cord can replace the tonic drive generated by the brain (Dimitrijevic et al., 1998). Another important indication that experimental models used to study the supraspinal control of locomotion need to be evaluated cautiously came from pioneers in the field. According to their observations, “destruction of the MLR results in some dyscoordination of hindlimb movements during walking and these cats do not run. Thus the MLR seems not to be necessary either for the initiation of locomotion or for walking in the intact animal” (Shik and Orlovsky, 1976, p. 477). This statement poses a big question on the whole epoch of studying the decerebrate cat or isolated preparations of the lower vertebrates in conjunction with understanding the locomotor control in intact brain. The approach to study locomotion is far from natural by necessity. Decerebration does not resonate with any normal functioning physiological network. Using an isolated, artificially perfused brain or brain slabs only exacerbates these limitations. Any mechanism revealed by these studies is of great value, of course, but their applicability to the awake-behaving organisms of greater complexity is restricted. An experimental study of motor control has been performed for decades. It is hard to deny a methodical progress, increasing of accuracy, and documenting the details of this process. There is also a theoretical approach with modeling attempts. The question remains: in what units should we measure the progress in studying the problem? Publications multiply in every decade, but do they get us closer to understanding the basic principles of functioning of complex neural networks called ‘the brain’? Taking into account the whole body of existing experimental data do we understand the supraspinal control of locomotion? Cautious optimism has been gradually followed by sober realism. Redoing old experiments in the hope of obtaining principally new results might be an attempt where failure is programmed from the beginning. Using alternative approaches is the plausible solution. Turning attention away from any unusual or too difficult to comprehend hypothesis

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might be not helpful. Constructive criticism is needed instead of ignoring even the slightest opportunity to get to the core of the problem. The new theoretical concept of neural optimal control, described in the previous chapter, can and should be applied to reinterpret the cited in this review data regarding the initiation of locomotion (Figure 4). The activity of the CPG, a ‘lower’ NOCS, can be characterized as initiated by simple tonic commands from the ‘higher’ NOCS, a network which does not have all the features that each limb CPG network has. Instead, it cares about muscle tone and interlimb coordination on the real terrain. The exact location of this ‘higher’ NOCS in the brain stem can be defined only vaguely, since NOCS is presumably a functional not a morphological unit. Nevertheless, this neural network exists in real space, partially coinciding with mRF. In turn, this network is a controlled object, a ‘lower’ NOCS for the ‘higher’ NOCSs - MLR and HLR. They send downstream tonic initiating signals to the network located in mRF without intrusion into the process of how stepping is performed, or how two or four legs are coordinated. Instead, their level of motor regulation is speed and type of locomotion, accompanied by controlling the heart rate, and the level of blood pressure needed to perform the function. Going even higher, the basal ganglia and cerebral cortex have the internal models of MLR and HLR as their ‘lower’ NOCSs (Figure 4), and they solve different problems on their level of motor control competence – where to go and why, but not how to do it. According to the new concept, there is no need to divide downstream signals to ‘specific’ and ‘non-specific’ types; they are either ‘initiating’ or ‘informational’. Identification of different types of signals - initiating and informational - coming in and out of locomotor regions along with defining their chemical nature would be the immediate experimental task which ideally should be performed in the monkey, but with full understanding the limitations of data interpretation, could also be done in lower animals. It is quite possible that these data already exist. They need to be found and put into the right place. Reinterpretation of existing experimental data along with getting new data looks like a fruitful approach. It is remarkable that some resonating

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features of explanation could be found in studies when authors were not familiar with the new optimal control concept (at least they did not refer to it). For example, it has been suggested that neural circuits are shared at the level of both the brainstem and spinal cord to the extent that the same neurons involved in regulating locomotion are similarly involved during reaching behavior (Drew et al., 2004). In other words, NOCSs for locomotion and reaching are two regimes of activity of virtually the same neural network. Adding scratching to these (Baev and Shimansky, 1992) brings the number of possible regimes to three with no restrictions for further increase. The statement that motor patterns available at birth are subject to maturation and modified substantially through learning (Grillner and Wallen, 2004) can be rephrased in a way that each NOCS is a learning system and “the learning process starts when the error signal increases and stops when it is minimized” (Baev, 1997). It is important to note that one of the widely known investigators of CPG, the innate structure for automatism, came forward with the conclusion that the dichotomy of innate versus learned movements is false, e.g., all motor patterns should be considered as voluntary, flexible, and subject to learning (Grillner and Wallen, 2004). The new concept provides, in our opinion, the concrete mechanism for such learning. Overviewing experimental data on the integration of multiple motor segments for the elaboration of locomotion, another group has formulated the puppet hypothesis (Mori et al., 2004). The monkey is conceptualized as a puppet with multiple motor segments that must be coordinated in time and space to accomplish a required motor action. According to the optimal control concept, motor segments are NOCSs of different levels. Principles of their hierarchical interactions have already been described in great detail (Baev, 1997, 1998). In this case, the new concept has already predicted the results of future experiments. Finally, there is no contest of what approach is better than the other. The best concept will be the one which produces practical results in building gadgets that mimic the activity of broken neural networks. It is for the future to designate what kind of prosthetic devices will be mostly in

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use – a robot which directly controls limb muscles or a device which modulates downstream tonic supraspinal influences, or pharmacological agents /deep brain stimulation which affect higher motor control centers to modify the activity of brainstem and spinal cord neural networks.

ACKNOWLEDGMENT This work was supported by a grant from National Institutes of Health P30 EY12196.

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In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 4

THE BRAINSTEM AND MOTOR COORDINATION Robert Lalonde University of Rouen, Department of Psychology EA7475, Mont-Saint-Aignan, Cedex, France

ABSTRACT Deficits in motor coordination have been reported at midbrain, pontine, and bulbar levels. In particular, deficits are prominent in patients with Parkinson's disease and have been reproduced in animal models of this disease caused by injections of neurotoxic agents such as 6-OHDA and MPTP. At the pontine level, the pedunculopontine tegmentum and the nucleus reticularis tegmenti pontis have been identified as regions involved in motor coordination in rats. At the bulbar level, the inferior olive has been identified as a brain region involved in motor coordination in rats and mice. Further experiments must delineate the cortico-subcortical circuits that characterize such deficits. 

Corresponding Author Email: [email protected], TEL: +33 02 35 14 61 08, FAX: +33 02 35 14 63 49.

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1. MIDBRAIN 1.1. Parkinson's Disease 1.1.1. Neuropathology Parkinson's disease (PD) causes degeneration of midbrain dopamine neurons in substantia nigra pars compacta and ventral tegmental area, which depletes dopamine levels in striatum, nucleus accumbens, and prefrontal cortex (Marsden, 1989; Miller and DeLong, 1988; Schneider and Obeso, 2015). The cardinal symptoms comprise akinesia/bradykinesia, muscular rigidity, and resting tremor, mitigated at different degrees with dopamine replacement therapy (Spiegel et al., 2014). Relative to controls, PD patients are often impaired in motor coordination tasks involving the use of hands or arms (Gorniak et al., 2013a; Huang et al., 2012; Ma et al., 2012; Park et al., 2012) and feet (Williams et al., 2013), under bimanual (Byblow et al., 2002; Lazarus et al., 1992; Verheul and Geuze 2004; Ponsen et al., 2006; Serrien et al., 2000; van den Berg et al., 2000) or interdigital (Rearick et al., 2002) conditions, as well as the control of posture (Adkin et al., 2005; Horak et al., 1992; Stuart et al., 2016), the synchronization between arm, hand, and torso (Bertram et al., 2005), arm and torso (Poizner et al., 2000), fingers, wrist, and arm (Teulings et al., 1997), eye and head (White et al., 1988), or upper and lower limbs (Albert et al., 2010; Swinnen et al., 1997). Deficits were also evident when subjects switched between movement patterns (Brown and Almeida, 2011; Geuze, 2001). In addition, PD patients showed defective sensorimotor learning in bimanual figure drawing (Swinnen et al., 2000) and forearm flexion-extension movements (Verschueren et al., 1997). The patients’ visuomotor tracking deficits with upper limbs were correlated with those regarding gait (Inzelberg et al., 2008). Likewise, the extent in deficiency of motor coordination while walking was correlated with freezing of gait (Peterson et al., 2012). Subjects with a history of falling had a higher degree of disease severity and worse impairments in lower-limb coordination, ability to rise from a chair, proximal lower-limb

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motor control, ambulation, motor planning of the hands and feet, and dynamic balance as measured by the ability to walk in tandem (Dennison et al., 2007). Recurrent fallers were also more prone to deficits in dual-task paradigms reflecting executive functions (Plotnik et al., 2011). Likewise, gait asymmetry worsened under dual-task conditions (Yogev et al., 2007). Indeed, gait disturbances are linked with a variety of cognitive dysfunctions (Stuart et al., 2016). These correlations may be explained by a common factor linking these deficits, namely striatal dopamine levels, concordant with findings that dopamine replacement therapy improves motor coordination (Bowen et al., 1973; Park et al., 2014). However, motor coordination of the hand appears to have both l-dopa-responsive and l-dopa unresponsive components (Benice et al., 2007). Gait disturbances were linked to decreased cholinergic activity in sensorimotor cortex based on the technique of transcranial magnetic stimulation (Pelosin et al., 2016). Although deep brain stimulation (DBS) of the subthalamic nucleus is used to treat gross motor dysfunctions, it was ineffective in improving fine motor coordination (Gorniak et al., 2013b). 1.1.2. Animal Models Neurotoxic agents have been applied as animal models of PD (Table 1), mainly 6-hydroyxydopamine (6-OHDA) and methyl-phenyltetrahydropyridine (MPTP). Peripherally injected MPTP is liable to cause visible gait disturbances in mice (Tillerson and Miller, 2003; Tillerson et al., 2002; Wang et al., 2012). To quantify such disturbances, motor coordination tasks have been designed, such as the stationary beam, the inverted grid, the staircase, the vertical pole, the inverted grid, and the rotorod (Huston and Bures, 1976; Jones and Roberts, 1968; Lalonde and Strazielle, 2013; Whishaw et al., 2008). In the stationary beam test, animals move along a homogeneously narrow surface made of wood or plastic. In more challenging tasks, beam widths are progressively narrowed or a slippery metal grid is placed over the beam (Glajch et al., 2012; McFarland et al., 2013). The number of segments crossed or the number of slips is measured as well as latencies before crossing the beam or falling.

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Stationary beam performance was deficient after peripherally injected MPTP in mice (Jayaraj et al., 2014; Sikorska et al., 2014). Table 1. Motor coordination deficits in rats and mice injected with the dopamine-depleting agents 6-hydroyxydopamine (6-OHDA) or methyl-phenyl-tetrahydropyridine (MPTP)

Neurotoxic agents

Tests

References

MPTP

stationary beam

6-OHDA

stationary beam

6-OHDA MPTP

inverted grid vertical pole

6-OHDA MPTP MPTP

vertical pole stair-climbing rotorod

6-OHDA

rotorod

Jayaraj et al., 2014; Sikorska et al., 2014 Glajch et al., 2012; McFarland et al., 2013; Smith et al., 2012 Smith et al.,, 2012 Diguet et al., 2005; Luchtman et al., 2012 Glajch et al., 2012 Viaro et al., 2010 Colotla et al., 1990; Duan and Mattson, 1999; Filali and Lalonde, 2016; Kawasaki et al., 2007; Luchtman et al., 2005, 2012; Rozas et al.,1998a,b; Shiotsuki et al., 2010; Viaro et al., 2010 Alvarez-Fischer et al., 2008; Heuer et al., 2012, 2013; McFarland et al., 2013; Monville et al., 2006; Ogura et al., 2005; Rozas et al., 1997; Smith et al., 2012; Thornton and Vink, 2012; Yoon et al., 2012;

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Likewise, unilateral 6-OHDA injections in the medial forebrain bundle, forming the nigro-striatal pathway, caused deficits in the stationary beam task in mice (Glajch et al., 2012; Smith et al., 2012). Beam deficits were also revealed after bilateral 6-OHDA injections in the substantia nigra pars compacta in rats (McFarland et al., 2013). However, MPTP had no effect on mouse stationary beam performance at a dose schedule which slowed down rotorod acquisition (Filali and Lalonde, 2016). In the inverted grid test, mice are placed on a horizontal grid turned over at an angle of 180. Unilateral 6-OHDA injections in the dorsal striatum caused deficits in the inverted grid test in mice (Smith et al., 2012). In the vertical pole test, the time taken to orient downwards towards the home cage and traverse the pole are measured. Peripherally injected MPTP combined with 3-nitropropionic acid (3-NP, an inhibitor of succinate dehydrogenase) caused deficits in the vertical pole test in mice (Diguet et al., 2005). Furthermore, peripherally injected MPTP combined with probenecid (delaying MPTP metabolism) caused deficits in the vertical pole test in mice (Luchtman et al., 2012). Moreover, unilateral 6OHDA injections in the medial forebrain bundle caused deficits in the vertical pole task in mice (Glajch et al., 2012). In the stair-climbing test, food-deprived animals are placed at the bottom of a staircase and climb to the top for a food pellet. Peripherally injected MPTP slowed down stairclimbing in mice (Viaro et al., 2010). In the rotorod test, animals walk or run on a moving beam and latencies before falling are measured. Peripherally injected MPTP (Colotla et al., 1990; Duan and Mattson, 1999; Filali and Lalonde, 2016; Kawasaki et al., 2007; Luchtman et al., 2005; Shiotsuki et al., 2010; Viaro et al., 2010), 3-NP (Fernagut et al., 2004), MPTP combined with 3-NP (Fernagut et al., 2004), MPTP combined with acetaldehyde (Rozas et al., 1998a,b), or MPTP combined with probenicid (Luchtman et al., 2005, 2012) caused deficits on the rotorod test in mice. Peripheral MPTP had no effect in the rotorod test in mice in one study (Tillerson et al., 2002) and only approached significance at p < 0.07 in another (Sedelis et al., 2000), perhaps due to different dose schedules, mouse strain or age, bar width, or other methodological factors (Sedelis et al., 2001). In any event, unilateral

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6-OHDA injections in the substantia nigra pars compacta, the medial forebrain bundle, or the dorsal striatum also caused rotorod deficits in mice (Heuer et al., 2012; Smith et al., 2012). Other researchers have confirmed the deleterious impact of unilateral 6-OHDA injections in the medial forebrain bundle on the rotorod in mice (Heuer et al., 2013) and rats (Monville et al., 2006; Rozas et al., 1997; Yoon et al., 2012) as well as unilateral 6-OHDA injections in the dorsal striatum of mice (AlvarezFischer et al., 2008) and rats (Monville et al., 2006; Thornton and Vink, 2012). As expected, bilateral 6-OHDA injections in the substantia nigra pars compacta (McFarland et al., 2013) or medial forebrain bundle (Ogura et al., 2005) caused deficits in the rotorod test in rats. In addition to neurotoxic agents, motor defects on rotorod, stationary beam, and grid tests have been described in genetically modified models of Parkinson's disease, notably wild-type and mutated mice overexpressing SNCA, encoding alpha-synuclein (Lalonde and Strazielle 2007).

2. PONTINE NUCLEI 2.1. Humans Motor symptoms associated with pontine lesions include paresis, ataxia, dysmetria, and dysarthria (Caplan, 2012; Maeshima et al., 2012; Schmahmann et al., 2004). Limb or facial paresis is caused by interrupted tracts from neocortex to brainstem or spinal cord, respectively. Ataxia, dysmetria, and dysarthria reflect cerebellar-like symptoms due to degeneration of a major cerebellar afferent. Hiraga et al., (2007) reported that ataxic hemiparesis is mainly caused by pontine or internal capsule lesions, but also after lesions of primary motor cortex with or without involvement of the postcentral gyrus, attributed to dysfunction of the fronto-ponto-cerebellar system.

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2.2. Animal Models In contrast to the midbrain, few experiments have been conducted on the lower brainstem. In one study, excitotoxic lesions of the pedunculopontine tegmentum (PPTg) decreased falling latencies on the rotorod in rats (MacLaren et al., 2014). On the contrary, no effect was found in rats after selective lesions of cholinergic neurons in PPTg caused by ethylcholine mustard aziridinium ion, AF64-A (Jun et al., 2016). In an isolated study, electrolytic lesions of nucleus reticularis tegmenti pontis (NRTP) in rats decreased time spent on a perpendicularly fixed board (Brudzynski and Mogensen 1984).

3. INFERIOR OLIVE 3.1. Humans The inferior olive may contribute to motor coordination deficits as a secondary consequence of cerebellar atrophy via retrograde degeneration of the olivo-cerebellar pathway. Ataxia and palatal tremor are common symptoms of hypertrophic olivary degeneration occurring after interruption of the cerebello-rubro-olivary pathway (Carvalho et al., 2016; Konno et al., 2016; Smets et al., 2017), commonly caused by vascular anomalies such as hemorrhage, malformations, and infarct as well as tumor, trauma, inflammation, demyelination, radiation, and Neuro-Behçet syndrome (Franco-Macias et al., 2015; Sabat et al., 2016; Zhang et al., 2015), but may also appear in the idiopathic form (Gu et al., 2015).

3.2. Animal Models Electrolytic lesions of the inferior olive often cause tremor, abnormal head posture, and an asymmetric trunk posture in rats (Modianos and Pfaff

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1976). Lesions of the inferior olive caused by 3-acetylpyridine combined with nicotinamide in the developmental period (Jones et al., 1995) or in adults (Wecker et al., 2013) impaired rotorod behavior in rats. The same effect was found in juvenile mice (Kotajima et al., 2014). Likewise, 3acetylpyridine combined with nicotinamide increased the time to cross a stationary beam and the number of balance corrections as measured by lateral tail movements in rats (Wecker et al., 2013). These experiments reflect cerebellar-like symptoms (Lalonde and Strazielle, 2013) resulting from destruction of one of its main afferent region. Indeed, cerebellar aspiration lesions in adult mice decreased latencies before falling on the rotorod (Goddyn et al., 2006). These latencies also decreased in transgenic mice overexpressing molecular systems for inducible or reversible inactivation of synaptic transmission in Purkinje cells (Karpova et al., 2005) and in mice with spontaneous mutations causing selective damage to Purkinje cells, such as nervous (Lalonde and Strazielle, 2003) and Agtpbp1pcd (Purkinje cell degeneration) (Le Marec and Lalonde 1997), as well as those with additional damage to cerebellar granule cells such as Grid2Lc (Lurcher ), Grid2ho-nancy (hot-foot), and Rora sg (staggerer ) (Lalonde and Strazielle, 2013).

CONCLUDING REMARKS Further experiments must delineate the subcortical circuits that characterize such deficits. For this purpose, experimental designs must be prepared to determine the impact of lesions at midbrain, pontine, and bulbar levels in conjunction with those of the cerebellum, dorsal striatum, and neocortex, on specific motor coordination tests such as the rotorod. It is likely that a basal ganglia circuit can be delineated along with a cerebellar circuit. Rotorod performance may depend on a single circuit comprising both, whereas other tests may be dependent on separate circuits.

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Sikorska, M; Lanthier, P; Miller, H; Beyers, M; Sodja, C; Zurakowski, B; Gangaraju, S; Pandey, S; Sandhu, JK. anomicellar formulation of coenzyme Q10 (Ubisol-Q10) effectively blocks ongoing neurodegeneration in the mouse 1-methyl-4-phenyl-1,2,3,6tetrahydropyridine model: potential use as an adjuvant treatment in Parkinson's disease. Neurobiol Aging, 2014, 35, 2329-46. Sindhu, KM; Saravanan, KS; Mohanakumar, KP. Behavioral differences in a rotenone-induced hemiparkinsonian rat model developed following intranigral or median forebrain bundle infusion. Brain Res, 2005, 1051, 25-34. Smets, G; Lambert, J; Tijssen, M; Mai, C; Decramer, T; Vandenberghe, W; Van Loon, J; Demaerel, P. The dentato-rubro-olivary pathway revisited: New MR imaging observations regarding hypertrophic olivary degeneration. Clin Anat, 2017, 30, 543-9. Smith, GA; Heuer, A; Dunnett, SB; Lane, EL. Unilateral nigrostriatal 6hydroxydopamine lesions in mice II: predicting l-DOPA-induced dyskinesia. Behav Brain Res, 2012, 226, 281-92. Spiegel, J; Uhrig, I; Krick, C; Behnke, S; Fassbender, K; Dillmann, U. Performance of repetitive alternating elbow movements in Parkinson's disease. Eur Neurol, 2014, 71, 84-8. Stuart, S; Lord, S; Hill, E; Rochester, L. Gait in Parkinson's disease: A visuo-cognitive challenge. Neurosci Biobehav Rev, 2016, 62, 76-88. Swinnen, SP; Steyvers, M; Van Den Bergh, L., Stelmach, GE. Motor learning and Parkinson's disease: refinement of within-limb and between-limb coordination as a result of practice. Behav Brain Res, 2000, 111, 45-59. Swinnen, SP; Van Langendonk, L; Verschueren, S; Peeters, G; Dom, R; De Weerdt, W. Interlimb coordination deficits in patients with Parkinson's disease during the production of two-joint oscillations in the sagittal plane. Mov Disord, 1997, 12, 958-68. Teulings, HL; Contreras-Vidal, JL; Stelmach, GE; Adler, CH. Parkinsonism reduces coordination of fingers, wrist, and arm in fine motor control. Exp Neurol, 1997, 146, 159-70.

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Thornton, E; Vink, R. Treatment with a substance P receptor antagonist is neuroprotective in the intrastriatal 6-hydroxydopamine model of early Parkinson's disease. PLoS One, 2012, 7(4), e34138. Tillerson, JL; Miller, GW. Grid performance test to measure behavioral impairment in the MPTP-treated-mouse model of parkinsonism. J Neurosci Methods, 2003, 123, 189-200. Tillerson, JL; Caudle, WM; Reverón, ME; Miller, GW. Detection of behavioral impairments correlated to neurochemical deficits in mice treated with moderate doses of 1-methyl-4-phenyl-1,2,3,6tetrahydropyridine. Exp Neurol, 2002, 178, 80-90. van den Berg, C; Beek, PJ; Wagenaar, RC; van Wieringen, PC. Coordination disorders in patients with Parkinson's disease: a study of paced rhythmic forearm movements. Exp Brain Res, 2000, 134, 17486. Verheul, MH; Geuze, RH. Inter-limb coupling in bimanual rhythmic coordination in Parkinson's disease. Hum Mov Sci, 2004, 23, 503-25. Verschueren, SM; Swinnen, SP; Dom, R; De Weerdt, W. Interlimb coordination in patients with Parkinson's disease: motor learning deficits and the importance of augmented information feedback. Exp Brain Res, 1997, 113, 497-508. Viaro, R; Marti, M; Morari, M. Dual motor response to l-dopa and nociceptin/orphanin FQ receptor antagonists in 1-methyl-4-phenyl1,2,5,6-tetrahydropyridine (MPTP) treated mice: paradoxical inhibition is relieved by D(2)/D(3) receptor blockade. Exp Neurol, 2010, 223, 473-84. Wang, Q; Qian, L; Chen, SH; Chu, CH; Wilson, B; Oyarzabal, E; Ali, S; Robinson, B; Rao, D; Hong, JS. Post-treatment with an ultra-low dose of NADPH oxidase inhibitor diphenyleneiodonium attenuates disease progression in multiple Parkinson's disease models. Brain, 2015, 138, 1247-62. Wang, S; Jing, H; Yang, H; Liu, Z; Guo, H; Chai, L; Hu, L; Tanshinone, I. selectively suppresses pro-inflammatory genes expression in activated microglia and prevents nigrostriatal dopaminergic neurodegeneration

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in a mouse model of Parkinson‫׳‬s disease. J Ethnopharmacol, 2015, 164,247-55. Wang, XH; Lu, G; Hu, X; Tsang, KS; Kwong, WH; Wu, FX; Meng, HW; Jiang, S; Liu, SW; Ng, HK; Poon, WS. Quantitative assessment of gait and neurochemical correlation in a classical murine model of Parkinson's disease. BMC Neurosci, 2012, 13, 142. Wecker, L; Engberg, ME; Philpot, RM; Lambert, CS; Kang, CW; Antilla, JC; Bickford, PC; Hudson, CE; Zesiewicz, TA; Rowell, PP. Neuronal nicotinic receptor agonists improve gait and balance in olivocerebellar ataxia. Neuropharmacology, 2013, 73, 75-86. Whishaw, IQ; Li, K; Whishaw, PA; Gorny, B; Metz, GA. Use of rotorod as a method for the qualitative analysis of walking in rat. J Vis Exp, 2008 Dec 10 (22), pii: 1030. White, OB; Saint-Cyr, JA; Tomlinson, RD; Sharpe, JA. Ocular motor deficits in Parkinson's disease. III. Coordination of eye and head movements. Brain, 1988, 111, 115-29. Williams, AJ; Peterson, DS; Earhart, GM. Gait coordination in Parkinson disease: effects of step length and cadence manipulations. Gait Posture, 2013, 38, 340-4. Winter, C; von Rumohr, A; Mundt, A; Petrus, D; Klein, J; Lee, T; Morgenstern, R; Kupsch, A; Juckel, G. Lesions of dopaminergic neurons in the substantia nigra pars compacta and in the ventral tegmental area enhance depressive-like behavior in rats. Behav Brain Res, 2007, 184,133-41. Yogev, G; Plotnik, M; Peretz, C; Giladi, N; Hausdorff, JM. Gait asymmetry in patients with Parkinson's disease and elderly fallers: when does the bilateral coordination of gait require attention? Exp Brain Res, 2007, 177, 336-46. Yoon, HH; Lee, CS; Hong, SH; Min, J; Kim, YH; Hwang, O; Jeon, SR. Evaluation of a multiple system atrophy model in rats using multitracer microPET. Acta Neurochir , 2012, 154, 935-40. Yurek, DM; Flectcher, AM; Kowalczyk, TH; Padegimas, L; Cooper, MJ. Compacted DNA nanoparticle gene transfer of GDNF to the rat

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striatum enhances the survival of grafted fetal dopamine neurons. Cell Transplant, 2009, 18, 1183-96. Zhang, M; Ye, G; Deng, L; Xu, S., Wang, Y. A case of hypertrophic olivary degeneration after resection of cavernomas of the brain stem and review of the literature. Neuropsychiatr Dis Treat, 2015, 11, 26138.

In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 5

THE BRAINSTEM AND REACHING-AND-GRASPING Claudia L. R. Gonzalez1, and Jason W. Flindall1 1

The Brain in Action Laboratory, Department of Kinesiology, University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4

ABSTRACT Reaching and grasping in humans is closely tied with vision; we use vision to plan, guide, and adjust reach to grasp actions as they unfold. Visual information for action is processed in the cortex along the dorsalvisual stream, which projects from the occipital to the parietal lobe. However, brainstem structures (in particular the superior colliculus) represent critical links in a secondary visual pathway, one that allows for the production of skilled movement in the event the dorsal-visual stream is damaged. In this chapter we discuss the evidence delineating the mammalian brainstem’s role in the guidance of skilled action in rodents, primates, and humans. In addition, we discuss studies that suggest the brainstem’s involvement in the selection of context-specific movements 

Corresponding Author Email: [email protected].

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1. INTRODUCTION Reaching and grasping are fundamental components of our everyday lives. We are constantly pointing to things, people, and locations, and we reach-to-grasp for objects hundreds of times a day. Simply put, it is through reaching and grasping that we manipulate our environment and shape it to fit our needs. In humans and non-human primates these actions are primarily guided by vision; so much so that, in fact, it has been argued that vision evolved specifically to allow the distal control of action. Over the past 50 years significant progress has been made to characterize the neural underpinnings of the reach-to-grasp action. When reaching out to pick an apple from a tree, visual information travels from the eye via the optic nerve to reach primary visual areas in the occipital cortex. Specifically, light reflected from the object strikes the retina, and triggers nerve cells to fire impulses that travel along the optic nerve to the optic chiasm. From there, inputs feed into the lateral geniculate nucleus (LGN) in the thalamus, which in turn provides input to the primary visual cortex (V1; aka striate cortex) in the occipital lobe. This route is dubbed the retino-geniculo-striate pathway, and is the dominant channel for visual information in primates, including humans. Obviously, in order to guide action, information about the apple’s size, shape and location need to be processed into an egocentric frame of reference (that is, a frame of reference with respect to the body, rather than with respect to the world, or to an outside observer). That transformation happens in the parietal cortex. After arriving in V1, visual information travels nearly everywhere in the brain, but we may simplify its path and say it travels both ventrally to the temporal cortex, and dorsally to the parietal lobe. The ventral path leading to the temporal cortex processes the visual information that allows us to identify objects and to form memories. This is the vision of which we are conscious – the “vision for perception” stream, as coined by Goodale

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and Milner (1992), allowing us to perceive the world around us and recognize objects and environments of which we are familiar. Alongside this pathway, the visual information from V1 also travels dorsally, to the parietal cortex, where it is translated into action-relevant terms. We are unconscious of the information processed by the dorsal stream – the “vision for action” network (Goodale and Milner, 1992) does not form memories but instead processes visual input on-line in order that we may produce movements to interact functionally with our environment. A viewed object’s location relative to the body determines how we reach out toward it; its absolute size and form determine how we must shape and orient our moving hands to capture it successfully. The dorsal stream is what allows us to translate vision into reaching and grasping. But what happens if visual information cannot reach the dorsal stream via V1? What if the primary visual cortex is damaged?

2. SUPERIOR COLLICULUS In the late 1960’s Nicholas Humphrey and Larry Weiskrantz published a paper describing the ability of two monkeys, Helen and Homer, who were able to reach and grasp for objects accurately (Humphrey and Weiskrantz, 1967). This ability would not be remarkable, were it not for the fact that these animals had undergone surgeries to remove their primary visual cortices completely. Humphrey reported that following her surgery, Helen behaved as if she were completely blind, one who “sat around listlessly, gazing blankly into the distance,” (Humphrey, 2009). However, after a minimal amount of training Helen was able to reach out and grasp a moving object and, eventually, navigate an obstacle-filled room while grasping food morsels off the floor. How was Helen able to “see” her environment and interact with it if she lacked any primary visual cortex? “The question remains as to what nervous structure may mediate the residual vision after striate lesions,” wrote Humphrey and Weiskrantz. “The obvious candidate is the superior colliculus,” a supposition based on electrophysiological recordings they had made in other animals around the

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same time. The superior colliculus (SC), part of the tectum within the brainstem, represents a gateway in the brainstem through which visual information may reach extrastriate cortical areas. Before the authors could confirm their speculation by lesioning Helen or Homer’s SC, Gerald Schneider published an article describing his own V1/SC lesion experiments, this time on hamsters (Schneider, 1969). In that paper, Schneider described how animals were trained on a visual orienting task, wherein they were to attend and orient to a sunflower seed brought near to them. They were also trained in a visual discrimination task where they learned to discriminate between card pairs on which were printed various discernable patterns. Card pairs might be black vs white, horizontally vs vertically striped, show different shapes, etc., and hamsters would learn that only one of the cards in such a pair would hide a food reward. Following the lesions, Schneider found that hamsters lacking the SC showed deficits only in the visual orienting task, and those without V1 showed impairment only in the visual discrimination task. Thus, Schneider was able to show a double-dissociation between mechanisms for two types of vision; one for determining the location of objects, and one for identifying objects. As in the primates, Schneider’s hamsters were able to locate objects sans V1, suggesting that visual information for the control of visually-guided action may have an alternate route, one that bypasses primary visual cortex, a route that passes through the brain stem. Schneider dubbed this route the retino-tectal-pulvinar pathway, as it travels through the tectum (which contains the SC) and the pulvinar nucleus of the thalamus.

3. CORTICO-SUBCORTICAL CIRCUITS The role of the superior colliculus in grasping is not limited to the simple transmission of visual information. The primary motor cortex (M1), premotor cortex [both dorsal (PMd) and ventral (PMv) aspects], and posterior parietal cortex [including both anterior (AIP) and medial (MIP) intraparietal areas] form the “lateral grasping network,” which is associated

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with the production and control of reaching and grasping movements (Borra et al., 2012). Notice that this network does not explicitly include any brainstem nuclei. However, direct recording studies of intermediate and deep neurons within the SC (and even deeper neurons, in the brainstem’s reticular formation) show that they are also active immediately prior-to and during reaching movements. In addition, direct stimulation to the SC can elicit reaching movements in stationary animals, or disrupt those already in progress. Why? In the macaque, the superior colliculus receives widespread inputs. These inputs project to different layers – that is, the superficial, intermediate, and deep layers of the SC all receive input from different networks. Superficial layers mainly receive inputs from regions associated with oculomotor control, i.e., those regions that control saccadic eye movements. These include the early visual areas (V1, and recipients of V1 output), the frontal and supplementary eye fields (FEF and SEF, respectively), as well as the lateral intraparietal cortex (LIP). The intermediate and deep layers of the SC receive input from the ventrolateral prefrontal cortex and from the lateral grasping network (Borra et al. 2012). Deep layers also receive input from orofacial regions of M1 (Tokuno et al. 1995). Circuits linking the inferior parietal area PFG and frontal area F5 in the macaque (involved with the selection of actions based on their endgoal) and circuits linking the AIP and F5 area (which are critical for transforming visuomotor information into movements based on object affordances) both project to the intermediate and deep layers of the SC. Saccadic information from the central visual field (via FEF) and peripheral visual fields (via area LIP) also makes its way to the deep and intermediate layers of the lateral SC (Distler and Hoffmann, 2015). While the reported strength of these connections vary from study to study (and layer to layer), they collectively demonstrate that the macaque superior colliculus receives a) polysensory information coming from peripersonal space in the lower visual field, and b) motor information related to arm, hand, and orofacial movements. Taken together, this implies that the SC is capable of not only the selection of context-appropriate grasping actions, but their execution as well. The SC therefore represents an integral link in a parallel system for

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the production of reaching and grasping movements, alongside the lateral grasping network. In addition to the SC, animal studies have demonstrated the importance of other brainstem structures in the production of motor behaviours. The rubrospinal and reticulospinal tracts are well known for contributing to the control of proximal musculature and gross motor behaviours, such as locomotion and posture. Both the rubruspinal and reticulospinal tracts originate within the brainstem; specifically, in the red nucleus and the reticular formation, respectively. Projections from both tracts terminate in close proximity to those of the lateral corticospinal tract, the major bundle of axons that project from motor cortical areas to the spinal cord. In fact, it has been demonstrated that behavioural recovery from spinal cord injury or motor cortex lesions depends on the integrity of the rubrospinal tract. Siegel et al. (2015) produced complete corticospinal tract lesions in mice and discovered that spontaneous behavioural recovery was associated with extensive new rubrospinal projections. If these new projections were removed, recovery was hindered, whereas enhancement of the projections led to enhanced recovery. With respect to the reticulospinal tract, a recent study in rats demonstrated that axons originating from the forelimb region of the sensorimotor cortex and traveling through the reticulospinal tract make extensive contacts with the spinal cord at the cervical level (Mitchell et al., 2016). Another study in non-human primates found robust activation of the reticular formation during a finger movement task, demonstrating the reticular formation’s role in the control of hand movements (Soteropoulos et al., 2012). Recent studies therefore are starting to highlight the crucial role that the rubrospinal and reticulospinal pathways play in the control of distal musculature, especially of the fingers and hand. In one such study, Alstermark and Pettersson (2014) severed a section of the corticospinal tract in rats and assessed the animals’ ability to reach out and grasp a piece of food. Surprisingly, the lesions had little to no effect on the rats’ success in retrieving the food. The authors suggested that the rubrospinal and reticulospinal tracts were likely candidates responsible for the spared ability. Earlier studies have reported that red nucleus lesions change the architecture of upper limb movements in the rat. These lesions

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result in abnormal adduction of the elbow and the wrist during a reach-tograsp task (Whishaw et al., 1998). Damage to the rubrospinal and reticulospinal pathways in cats and non-human primates also result in reaching and grasping deficits (Alstermark and Isa, 2012). The extent of the deficit depends on the location at which the transection occurs; transections affecting the rubrospinal tract at the level of the cervical segment 2 (C2) affect reaching and grasping movements, whereas lower transections (at the C5 level) result in grasping impairments but normal reaching movements. This dichotomy is due to a critical projection of interneurons at the C3-C4 level that connect to the reticulospinal pathway and the motor neurons of the spinal cord. Outside the rubrospinal and reticulospinal pathways, recent advancements in technology have allowed the direct demonstration that other brainstem structures are important to the production of reaching and grasping movements. In 2014, Maria Esposito and her colleagues completely ablated the brainstem nucleus medullary reticular formation ventral part (MdV) and analyzed the performance of these mice in several motor tasks (Esposito et al., 2014). The animals were indistinguishable from controls in running on a cage wheel, walking across a horizontal ladder, and general cage behaviour. However, severe deficits were found in two skilled motor tasks. First, when placed on a rotating drum (aka a “rotarod”) animals were unable to adjust their forward speed to match that of the drum and they fell quickly; much like a clumsy lumberjack would fall from a waterborne log. For the second task, animals had to learn to reach out, grasp a food pellet on a shelf, and bring it to the mouth. Animals with depleted MdV neurons were unable to complete the single-pellet reaching task, despite extensive training. Further analyses revealed that MdV-depleted mice showed impairments in the pronation and grasping components of their movements, making it difficult or impossible to retrieve the food. An important note: the authors also showed that the MdV projects to motorneurons that innervate three muscles controlling arm and forearm movements in mice. Specifically, the biceps, extensor carpi radialis, and extensor digiti quarti muscles all receive input from MdV and are fundamental for the production of reaching and grasping movements.

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In sum, the results of these studies in mice, rats, cats, and non-human primates provide definitive evidence that brainstem structures are critical for skilled motor behaviours and in particular for reaching and grasping. But what about evidence in humans?

4. HUMAN NEUROPATHOLOGY While information related to reaching and grasping deficits in those suffering brainstem damage is limited, the brainstem’s involvement in transfer of visual information is better known. As one would expect, when a person suffers damage to V1, blindness is the inevitable result. Patients who have suffered partial damage to V1 via stroke or other traumatic event will present with hemianopia (i.e., blindness in a limited region of the visual field) coinciding with the area of V1 that was damaged (Weiskrantz et al., 1974). Counterintuitively, however, these patients may still show sensitivity to stimuli occurring within the blind hemifield. For example, they may make saccades to points of light appearing in the blind field, or correctly “guess” the path of an object passing through the blind field, despite their apparent inability to “see” anything in the field affected by injury. In 1987, Weiskrantz and his colleagues described this phenomenon of blindsight as an example of implicit processing, or “residual functioning in the absence of explicit knowledge ” (Weiskrantz, 1996). As it happens, blindsight is one of the best examples to demonstrate the brainstem’s ability to mediate reaching and grasping. Patient DF (Goodale et al., 1991) is arguably the most famous blindsight patient; she could not describe objects placed in front of her, identify line drawings of those objects, or estimate their absolute or relative size, but could nevertheless scale her grip accurately when she would reach to grasp physical targets. However, DF’s disability arose following damage to her ventral stream; her perceptual deficits came from damage that spared both her primary visual cortex and dorsal stream function. Another patient, GY, was famously able to trace the position of a moving stimuli manually in his

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blind visual field, as well as correctly report colour in that same blind field, while all the while maintaining that all of his responses were merely guesses (Weiskrantz, 1995). While the damage to his striate cortex was more complete than DF’s, he too had some spared cortex in V1 that (although unlikely) could have accounted for his blindsight abilities. In contrast, patient CB, whose abilities were described by Christopher Streimer and colleagues (Striemer et al., 2009), had a unilateral stroke that totally abolished his right-side V1, which of course resulted in complete loss of his left visual field. Nevertheless, CB was still sensitive to visual stimuli appearing within his blind hemifield, even if he was not specifically conscious of its presence. Just like healthy participants, CB showed redundancy gain – that is, when he was asked to push a button when an object appeared on a screen, he was quicker to react if the object appeared in both hemifields than when it appeared only on one side. In addition, CB will avoid obstacles placed in his blind hemifield when reaching to grasp an object placed in his sighted field. These results suggest that CB is able to capitalize on visual information in his blind hemifield even if he is not explicitly aware of doing so. While Streimer and colleagues were unable to provide functional imaging of CB’s brain, they suspected that the retino-tectal-pulvinar pathway was responsible for his blindsight abilities. Just as Schneider described it in his studies on hamsters, this pathway travels from the retina, through the superior colliculus in the tectum, to the pulvinar nucleus of the thalamus, ultimately projecting to area MT in humans. Area MT in turn projects to the dorsal stream in parietal cortex (Figure 1). Even patient GY (he who was able to trace the path of light in his blind visual field) was presumed to be acting on information passing through this pathway. Again however, no imaging data were available to confirm this presumption. With these data unavailable, we look to evidence from another blindsighted patient, SJ.

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Figure 1. Cortical and subcortical regions associated with the production of reaching and grasping actions, with an overlay representing important visual pathways. Abbreviations: V1 = primary visual cortex, aka striate cortex; MT/V5 = area MT, aka V5; M1 = primary motor cortex; LGN = lateral geniculate nucleus; SMA = supplementary motor area; SEF = supplementary eye fields; PMv = ventral aspect of premotor cortex; FEF = frontal eye fields; PMd = dorsal aspect of premotor cortex.

Patient SJ is another individual who could reach to grasp objects placed in her blind field, and accurately scale her grip aperture to those targets despite being unable to estimate their size manually (Whitwell et al., 2011). She could also reach-to-touch targets, and would accurately report a sensation of motion for moving but not stationary objects presented in her blind hemifield. Researchers working with SJ suspected that she too relied on the retino-tectal-pulvinar pathway to mediate her blindsight abilities. The researchers working with patient SJ were able to investigate their hypothesis via functional Magnetic Resonance Imaging (fMRI), a technique which measures the location of both oxygenated and deoxygenated blood in the brain via changes in a magnetic field projected around a person’s head. From the blood oxygen level dependent (BOLD) signal, scientists may infer activity in different brain regions. While scanning SJ’s brain, researchers found that BOLD response in areas MT

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and STS (another region sensitive to movement) was bilateral and robust when a visual stimulus was moving, even when presented to her blind hemifield. This finding explained SJ’s sensitivity to movement, despite the fact that she was unable to articulate when the stimuli in her blind field were present, let alone in motion. While it does not definitively prove that the retino-tectal-pulvinar pathway is responsible for her blindsight (after all, fMRI data were collected during passive watching, rather than active movement production), the fact that this pathway projects directly to MT is certainly suggestive. In primates, the retino-tectal-pulvinar pathway has become somewhat vestigial to the retino-geniculo-striate pathway and the dorsal stream. It is thought that the retino-tectal-pulvinar pathway reassumes primacy of function only when the retino-geniculo-striate pathway becomes damaged (Rodman et al., 1989, 1990). Thus, despite widespread cortical chauvinism – a belief that the cortex occupies a supreme and unassailable role in the control and production of action – we show instead that the preeminent place of primary visual cortex is provisional, with the brainstem ready to step up in time of need.

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Tokuno, H; Takada, M; Nambu, A; Inase, M. Direct projections from the orofacial region of the primary motor cortex to the superior colliculus in the macaque monkey. Brain Res., 1995; 703:217 - 22. Weiskrantz, L. Blindsight: not an island unto itself. Curr. Direct Psychological Sci., 1995; 4:146 - 51. Weiskrantz, L. Blindsight revisited. Curr. Op. Neurobiol., 1996; 6: 215 - 20. Weiskrantz, L; Warrington, EK; Sanders, M; Marshall, J. Visual capacity in the hemianopic field following a restricted occipital ablation. Brain, 1974; 97:709 - 28. Whishaw, IQ; Gorny, B; Sarna, J. Paw and limb use in skilled and spontaneous reaching after pyramidal tract, red nucleus and combined lesions in the rat: behavioral and anatomical dissociations. Behav. Brain Res., 1998; 93:167 - 83. Whitwell, RL; Striemer, CL; Nicolle, DA; Goodale, MA. Grasping the non-conscious: Preserved grip scaling to unseen objects for immediate but not delayed grasping following a unilateral lesion to primary visual cortex. Vision Res., 2011; 51:908 - 24.

In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 6

THE BRAINSTEM AND EYE MOVEMENTS: A FOCUS ON MOTOR AND PREMOTOR COMMANDS Olivier A. Coubard* The Neuropsychological Laboratory, CNS-Fed, Paris, France

ABSTRACT Here I revisit the Hering-versus-Helmholtz controversy on binocular coordination from the psychophysician’s description of combined saccade-vergence eye movements to the neurophysiological recording of motor and premotor neurons of oculomotor neural circuitry. While neoHeringians have accumulated arguments for separate saccade and vergence systems at both behavioral and neural premotor levels, neoHelmholtzians have also provided evidence for monocular programmed eye movements and commands at the premotor level. Bridging the two, I conclude that Hering and Helmholtz were both right. The latter’s viewpoint brings to the fore the importance of adaptive processes while the former emphasizes neurobiological constraints. *

Corresponding Author: The Neuropsychological Laboratory, CNS-Fed, Paris, France, Tel: 33145-493608, Email: [email protected].

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Keywords: vision, eye movements, motor control, binocular coordination, hering vs. helmholtz controversy

1. INTRODUCTION How are human eyes coordinated? Do saccade and vergence eye movements correspond to distinct information processing systems? This article is a review of these questions dating back to a controversy on binocular vision which developed in the nineteenth century between Ewald Hering (1834-1918) and Hermann von Helmholtz (1821-1894). Hering proposed that the eyes should not be seen as two separate organs but as two halves of a single organ, and that one and the same impulse of will directs both eyes simultaneously as one can direct a pair of horses with single reins (Hering, 1977). Hering conceptualized this single organ as a double or cyclopean eye placed midway between the two eyes and simplified the issue of binocular coordination. For a displacement in direction and in distance, the double eye receives two innervations, one to turn to the right or to the left, the other to verge for greater nearness or distance (Hering, 1977). This results in each eye receiving two equal innervations – the Hering law of equal innervation: one is a rotation of both eyes to the right or to the left, the other is a rotation of both eyes inward or outward. These two commands are supposed to be additive and occur simultaneously in each eye. Disagreeing with this hypothesis, Helmholtz suggested that the two eyes move independently from each other and that binocular coordination is a learned behavior (Helmholtz, 1924-1925). Let us consider a particular example of combined movement between two points aligned on one eye (Figure 1). Following Hering (Figure 1A), both eyes simultaneously receive two equal innervations. They receive an equal innervation in opposite directions to reduce convergence angle (ΔVerg): the left eye receives a command of rightward displacement, and the right eye receives a command of leftward displacement. Simultaneously, both eyes receive an equal innervation to turn to the left (ΔConj). Therefore the left eye remains in its initial position, whereas the

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right eye moves significantly to the left. Following this hypothesis, while only the right eye adductor (medial rectus) receives a command, two antagonistic commands act on the adductor (medial rectus) and abductor (lateral rectus) of the left eye. In line with this hypothesis, Hering notices that the left eye nevertheless undergoes a twitch, albeit counterproductive, that an observer can easily perceive (Hering, 1977). Following Helmholtz (Figure 2B), only the right eye receives an innervation to turn to the left (ΔOD) (Helmholtz, 1924-1925). This Hering-Helmholtz discussion centers on the question of binocular versus monocular commands. It also raises the issue of putative distinct conjugate and disconjugate modules. In this chapter, I will discuss the modularity of the mechanisms underlying saccades as an example of conjugate movement and vergence as an example of disconjugate movement. I will examine how the study of the dynamics of saccade, vergence, and saccade-vergence movements supplies information for the debate on distinct saccade and vergence systems at both behavioral and neurophysiological levels.

2. DISTINCT SACCADE AND VERGENCE SYSTEMS 2.1. Behavior 2.1.1. Saccade Dynamics From the ancient French word sachier meaning secouer (to shake), transformed to saquer (to pull), a saccade is a word taken from horseriding signifying the sudden shake given to the horse reins: by extension an abrupt movement, a jerk, a shock, a bound. Applied to eye movements, the saccade refers to the explosive movement suddenly modifying the line of sight. Historically, one attributes the first use of the term saccade in eye movements to Javal. In his Essai sur la physiologie de la lecture , Javal described progressive myopia that the series of saccades made during reading, responsible for the increase in myopic disability (Javal, 1879). Landolt (1891) observed that when the eye follows a straight line which is not interrupted by any object capable of catching its attention, the eye

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interrupts its excursion by a series of breaks; it moves in saccades, in steps (page 388). In 1903, Dodge established a classification of eye movements. For him, type I eye movements (saccades) are fundamental reactions to an eccentric retinal stimulation and dependent on the tendency developed in early life to move the eyes so that the object of interest is seen by the fovea (Dodge, 1903).

Figure 1. Eye movement in direction and in depth between two stimuli aligned on the left eye (with the two eyes open). (A) Combined eye movement of saccadeconvergence following Hering’s hypothesis. The two eyes receive two innervations: one of displacement inward to increase convergence angle (ΔVerg), the other of displacement to the left to move in direction (ΔConj). The double eye ( Doppelauge) is shown in the dotted line between the two eyes. Importantly in the seminal Hering’s proposal, the movement in distance and in direction is not serial but parallel. Indeed, the two innervations of displacement in distance and in direction are simultaneously addressed to both eyes. (B) Monocular saccade of the right eye following Helmholtz’s hypothesis. Only the right eye receives a command of displacement to the left (ΔRE). LE: left eye, RE: right eye. Adapted from Coubard, 2011, Les neurones des mouvements des yeux, Sarrebrücken: Editions Universitaires Européennes, page 10, Figure 2.

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Two parameters enable us to identify saccadic behavior unambiguously: its velocity and duration, both linked to saccade amplitude. A saccade is an extraordinary movement in that it can reach a velocity of 800 degrees per second in tens of milliseconds (Bahill et al., 1975). The greater saccade amplitude, the greater saccade duration and velocity. Using a photographic technique, Dodge and Cline (1901) observed that the duration of type I movements directly varies with movement angle. The linear relationship between peak velocity and amplitude for saccades up to 20 degrees, and between duration and amplitude for saccades up to 50 degrees, was formalized by Bahill et al. (1975) and called the main sequence, a term borrowed from astronomy referring to the tight relationship between star brightness and temperature. The main sequence enables researchers to identify as saccades some movements whose type may still be still unknown (Coubard and Kapoula, 2008). The prompt character of saccades obviously deserves our attention about the quality of such an abrupt change in the line of sight, that is to say movement accuracy. Inaccuracy or error or dysmetria corresponds to the difference between the actual eye position at the end of the saccade and the required position to reach the target. Dysmetria consists in either hypermetria (overshooting) whenever the eye exceeds target position or hypometria (undershooting) as soon as it remains below target position. For instance, saccades responding to two near targets appearing at the same time do not shoot any of these targets but occupies an intermediate position – this is the global effect (Findlay, 1982; Ottes et al., 1984). 

In brief, a saccade is a fast-striking movement whose execution can reach hundreds of degrees per second in around tens of milliseconds. Saccade velocity and duration parameters are little influenced by cognitive processes however accuracy may vary with the context in which the saccade is performed.

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2.1.2. Vergence Dynamics From the Latin word vergere meaning to incline, vergence as a servant of binocular coordination and bifoveal fixation consists in the alignment of visual axes on the object of interest. Under natural conditions, vergence is a complex phenomenon resulting from subtle responses to multiple stimulations (Han Collewijn and Erkelens, 1990; Judge, 1991; Leigh and Zee, 1999). Two main stimuli elicit vergence eye movements: disparity and blur. Disparity is the stimulation by the same object of disparate points on the two retinas so that the object is seen double (diplopia). One can experience disparity by successively gazing towards points aligned along the median axis. In such a case, a binocular movement of disparity or fusional vergence is required to see a single object. Blur is the absence of clarity of the perceived image and independently concerns one eye or the other. Blur may be experienced by covering one eye and successively fixating two objects aligned with the uncovered one. In such a case, a monocular movement of accommodative vergence is required to focus on the object of interest. In everyday life, other cues participate to vergence eye movements such as the feeling of nearness (Wick and Bedell, 1989) based on cues such as perspective (Enright, 1987), change in size (McLin et al., 1988), or movement-derived (Ringach et al., 1996). All these sources of information may interact and offer various complex problems to solve for vergence eye movements. The near triad for fixating a near object is a synkinesis of disparity convergence, accommodative vergence, and pupil contraction (Semmlow and Hung, 1983). Convergence and divergence correspond to type V movements in Dodge’s taxonomy (Dodge, 1903). Dodge defined these movements as reactions to eccentric stimulations in depth falling on disparate points on the two retinas so that eye movements are not in the same direction but opposite ones. Some vergence characteristic pointed out by Dodge is movement slowness, whose duration by 400 ms on average may even reach one second. Interestingly for Dodge, vergence is slow as each eye is delayed by its natural tendency to move in the same direction as the other. Disparity error is the most powerful signal to elicit vergence eye movements (Han Collewijn and Erkelens, 1990). Disparity vergence can

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be studied independently from accommodative vergence and from pupil contraction using a dichoptic stimulation device. In this device, some arrangement of projectors, polarizing filters, and optical pinholes enable patterns to be projected on a screen and to be visible by only one eye or the other. Westheimer and Mitchell (1956) were the first to show that disparity error on its own is sufficient to elicit vergence eye movements. In response to sudden changes in disparity amplitude of 1.5 to 6 degrees, the authors reported pure vergence movements with a duration of 400 ms to one second, which was later confirmed by Rashbass et Westheimer (1961). Erkelens et al. (1989) reported that such fusional vergence in response to a pair of targets simultaneously visible along the median axis is initially smooth and then mediated by a small saccade of unequal amplitude in the two eyes. Peak velocity varied with movement amplitude: it was 50 degrees per second for a 5-degree movement and reached 150-200 degrees per second for vergence changes up to 34 degrees. Vergence along the median axis follows the main sequence, though velocity may vary with the presence of saccades in the course of vergence (Hung et al., 1994). Convergence tends to be faster than divergence (Hung et al., 1997; Zee et al., 1992). Collewijn et al. (1995) reported that pure vergence, that is without any intruding saccades, is almost never observed despite some cautious adjustment of stimuli along the median axis. In particular, divergence is almost always associated with a saccade. Importantly, simultaneously visible targets (i.e., switched on at the same time) along the median axis induce perceptual confusion, causing ambiguous vergence. Ambiguous vergence is defined by Collewijn et al. (1995) as a movement of lower amplitude (about half the target eccentricity) than that required to reach the target, or a movement performed in two stages to reach the target, and almost mediated by intruding saccades. Such ambiguities mostly occur for vergence movements with amplitudes below 10 degrees and can efficiently be avoided by a vertical lag of one degree between the two targets in depth (Collewijn, et al., 1995). Perceptual ambiguity is reduced even more when targets are visible successively and not simultaneously. However the successive appearance of targets does not

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totally suppress saccades intruding in the course of vergence (Coubard and Kapoula, 2006, 2008). 

In brief, fusional vergence is distinct from saccades in that it is particularly slow. For mean amplitudes, its velocity does not reach one hundred degrees per second whereas that of saccades is in the range of several hundred degrees per second. Fusional vergence achieves its movement in either several hundred milliseconds or even one second, against only tens of milliseconds for saccades.

2.1.3. Saccade-Vergence Dynamics: Two Interacting Systems? Saccade-vergence defined as a combined movement of the eyes in direction and in depth is a valuable tool to investigate the modularity of saccade and vergence mechanisms. Though the terms saccade-vergence might intrinsically tend toward Hering’s hypothesis, it is for convenience that we use them in place of either disconjugate saccade or asymmetrical vergence keeping in mind that the modularity controversy is open. Why is saccade-vergence a valuable tool? If saccade and vergence were two independent systems, an eye movement in direction and in depth would correspond to the linear sum of a saccade and a vergence. This was the point made by Yarbus (1957, 1967). Using photographs of a beam of light reflected by a mirror attached to the eyeball, Yarbus proposed that the combined eye movement in the horizontal plane is triphasic. The movement is (i) initially a slow vergence, (ii) followed by a fast saccade, and (iii) a second slow vergence finishes the movement (Figure 2). Figure 2B shows two saccade-vergence movements. Saccadedivergence between points A and B is composed of: (i) a slow presaccadic divergence (A-C), during which the point of intersection of visual axes is displaced along the cyclopean axis directed to point A (the median axis); (ii) a saccade (C-D), that is a rotation of the cyclopean axis directed to point B associated with a slight divergence; (iii) a final divergence (D-B), during which the point of intersection of visual axes is displaced along the cyclopean axis now directed to point B. In the same way, saccadeconvergence movement between points B and A is composed by: (i) a slow

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presaccadic convergence (B-E), during which the point of intersection of visual axes is displaced along the cyclopean axis directed to point B; (ii) a saccade (E-F), that is a rotation of the cyclopean axis directed to point A associated with a slight convergence; (iii) a final convergence (F-A), during which the point of intersection of visual axes is displaced along the cyclopean axis now directed to point A. Except for the subtle vergence associated with saccadic movement, Yarbus suggests that the combined eye movement is a linear sum of saccade and vergence movements. Though Yarbus’ conception is in line with Hering’s hypothesis, the two viewpoints differ in that Yarbus (1967) proposes a serial process (the combined movement is a slow vergence, then a fast saccade, then again a slow vergence), while Hering (1977) suggests a parallel process. In this, Yarbus’ conception can be viewed as a radicalization of Hering’s hypothesis emphasizing the cooperative behavior of the eyes (Collewijn, et al., 1995).

Figure 2. Combined saccade-vergence movement by Yarbus. (A) Photographic recording of eyes’ position during a combined saccade-divergence movement (right eye in the upper part, and left eye in the lower part). (B) Schema of combined saccadedivergence movement between points A and B (left panel) and of combined saccadeconvergence movement between points B and A (right panel) built on the basis of oculomotor recordings. From Yarbus, 1967, Eye movements and vision , New York: Plenum Press, pages 154-155 (© Springer, with permission).

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Yarbus’ additivity hypothesis of saccade and vergence was challenged a few years later by several authors. The contest first concerned saccade conjugacy. Indeed, Ono and collaborators (Ono and Nakamizo, 1978; Ono et al., 1978) used Johannes-Müller’s experiment and reported significantly unequal saccades in the two eyes. In this experiment, the participant moves his/her eyes between two targets aligned with one eye, while the eye for which targets are not aligned is covered. Theoretically, only the open eye should move to accommodate on the target of interest, but a saccade is associated with the movement (Alpern and Ellen, 1956a, 1956b). Such a superfluous saccade is seen by Yarbus hypothesis’ advocates as additional evidence for the superimposition of saccadic and vergence commands. However Ono and Nakamizo (1978) and Ono et al. (1978) observed that saccades made by the two eyes are too unequal in magnitude and velocity to be only explained by the additivity hypothesis. Kenyon et al. (1980) examined saccadic intrusions in the course of symmetrical vergence and noticed that saccades are asymmetrical in a way that cannot be justified by the linear sum of a saccade and vergence movements. Enright (1984) studied combined eye movements in four participants between two real and continuously visible targets (the extremity of two needles). Reexamining and replicating Yarbus’ seminal experiment by using the same stimulation in direction (a 5-degree angle) and in distance (2-3 degrees), Enright found that though the triphasic description remains almost true, quantitative analysis of saccadic conjugacy revealed that the dissociation between saccades and vergence is not as clear-cut as originally reported by Yarbus. Then, manipulating different distances and eccentricities, Enright (1984) reported that most of the vergence movement occurs during the saccade (the intrasaccadic period): indeed, for a change in direction by 4 degrees and a change in distance below 1 degree, 90% of vergence occurs during the saccade; for changes by 9 degrees and 2.3 degrees in respectively direction and distance, it is 80% that occur during the saccade; finally, 40 to 60% of vergence is executed during the saccade when the eyes move by 0.9 degree in direction and 0.7 degree in distance. Enright concluded that saccades and vergence are not summed in combined eye movements but that they interact, the required eccentricity and vergence angle being the

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decisive factors of such an interaction. Later, Enright (1986) dissociated binocular and monocular stimulation and reported that some part of accommodative vergence also occurs during the saccade (though no displacement in direction is required), thus corroborating the studies by Ono et al. Erkelens et al. (1989) then Zee et al. (1992) confirmed the interaction between saccades and vergence during combined eye movements. Erkelens et al. (1989) exploited huge angles in their visual stimulation and reported differences between convergence and divergence. Indeed, when the eyes move 45 degrees in direction and 11 degrees in distance, 95% of divergence against 75% of convergence is accomplished during the saccade, and peak velocities of saccade-divergence significantly exceed those of saccade-convergence. The same team (Collewijn, et al., 1995) confirmed the highly integrated action of conjugate and disconjugate mechanisms by eliciting combined eye movements up to 65 degrees in direction and by 25 degrees in distance. In combined eye movements, vergence is accelerated and shortened by comparison to vergence along the median axis: 50 to 100% of divergence (against 40 to 70% of convergence) is executed during the saccade as a function of increasing version. Conversely, saccade is slowed down and delayed in combined eye movements compared to pure saccade between two points for which the vergence angle remains the same. Secondly, the challenge of Yarbus’ additivity hypothesis bears upon the symmetrical nature of vergence during pre- and post-saccadic periods of combined eye movements. In this, there remains some disagreement between Erkelens, Collewijin and Steinman’s team on the one hand, and Enright on the other. Examining the trajectories of the binocular fixation point (the intersection point of the two lines of sight) during combined eye movements, Collewijn et al. (1997) have suggested that the trajectory of the initial (presaccadic) vergence tends to follow an iso-directional line going through the target of origin (that is the line through the center of the cyclopean eye and the initial point of the movement). According to the authors, there is no change in direction before the saccade starts, and this seems to be the case for both the saccade-divergence and saccadeconvergence movements. In other words, the initial vergence of combined

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eye movements may be symmetrical, as initially proposed by Yarbus. However, Enright (1998) is in complete disagreement with this suggestion. Reexamining the data of Collewijn et al. (1997) along with some new data, Enright has concluded that neither the initial nor the final vergence (respectively the first and third phases in Yarbus’ triphasic description) of combined eye movements is symmetrical. The author also discusses contradictions between the two teams in terms of spatial arrangement of targets, data analysis, eye movement recording devices, and subject factor (Enright, 1998). 

In brief, most authors (Collewijn, et al., 1995; Enright, 1984; Erkelens et al., 1989) agree that saccade and vergence interact in combined eye movement. Much evidence shows that the main part of vergence is accomplished during the intrasaccadic period, significantly changing the dynamics of saccade and vergence during saccade-vergence, by comparison with either saccade or vergence performed in isolation. On the other hand, saccades and vergence may correspond to two information processing systems that are distinct but in strong interaction (Collewijn, et al., 1995, 1997; Zee, et al., 1992). However for Enright (Enright, 1984, 1986, 1998), there might not exist two distinct systems but the two eyes may be independently guided in response to their specific retinal stimulation.

2.2. Neurophysiology I now examine neurophysiological evidence related to the controversy opposing authors adhering to the conception of saccade and vergence commands equally received by the two eyes (Hering’s hypothesis) to those advocating for the viewpoint of monocular commands independently received by the two eyes (Helmholtz’s hypothesis).

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2.2.1. Saccade Neurons Extraocular muscles are directed by motoneurons. The lateral rectus is innervated by the abducens nerve (VI) whose somas sit lateral and beneath the fourth ventricle at the level of the pons. The superior oblique is innervated by the trochlear nerve (IV) whose somas are located in the mesencephalon, below the aqueduc at the level of the inferior colliculi. Other muscles (medial rectus, superior and inferior rectus, inferior oblique, and intrinsic muscles of the eye) are innervated by the oculomotor nerve (III) whose somas are situated in the mesencephalon, beneath the aqueduct, at the level of the superior colliculi. The oculomotor nucleus is made of big multipolar neurons lying longitudinally and innervating specific muscles. Saccades are generated by forces that consist of three components: pulse, step, and slide. The initial pulse force is a burst discharge for generating sufficient force to move the eye by counteracting the resistance inherent in eye viscosity in orbital tissues. Such a burst discharge is interpreted as a velocity command. The step force is a burst discharge to hold the eye at its new eccentricity against the elastic forces of the oculomotor plant (orbital tissues and muscles): it is interpreted as a position command. Finally, the slide force is embedded between the pulse and the step to neutralize long time-constant visco-elastic forces of the oculomotor plant (Collins et al., 1975; Miller and Robins, 1992). The pulse-slide-step discharge (or burst-tonic discharge) pattern of motoneurons generating horizontal saccades is produced by a complex of premotor neurons, also called the saccade generator. These premotor neurons are located (i) in the paramedian pontine reticular formation (PPRF) rostrally to abducens nucleus, (ii) in the contralateral medullary reticular formation (medRF) caudally and ventrally to abducens nucleus, (iii) in the bilateral nucleus prepositus hypoglossi (NPH), and (iv) in the medial vestibular nucleus (MVN) (Fuchs et al., 1985; Moschovakis et al., 1996; Scudder et al., 2002). The major source of the step force (position command) is achieved by bilateral NPH and adjacent MVN (Langer et al., 1986). The initial pulse force (velocity command) is itself produced by burst neurons of PPRF and of medRF. Burst neurons discharge at a high frequency around 10 ms before the start of the saccade and cease

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discharging just after the end of the saccade. Burst neurons of PPRF are excitatory burst neurons (EBN), which connect ipsilateral motoneurons and activate them for ipsilateral saccades. Burst neurons of medRF are inhibitory burst neurons (IBN), which contact contralateral motoneurons. EBNs and IBNs discharge for horizontal saccades in an ipsilateral direction (Fuchs et al., 1985). Specific EBNs also exist for vertical saccades, which are found in the rostral interstitial nucleus of medial longitudinal fasciculus (riMLF) (Büttner-Ennever and Büttner, 1978; King and Fuchs, 1979). Premotor neurons are under the inhibitory control of a neural network consisting of pause neurons. These neurons are confined in a tight nucleus within the PPRF, oriented dorsoventrally and extending both sides of the median axis between descending rootlets of the abducens nerve– also called the nucleus raphe interpositus (Büttner-Ennever et al., 1988). Pause neurons project to burst neurons on which they exert tonic inhibition (Fuchs, et al., 1985). They discharge at a high frequency when the eyes are fixating and cease discharging during saccades in all directions. For that reason, they are called omnidirectional or omnipause neurons. Accordingly, to initiate a saccade, pause neurons must be inhibited and remain so for the entire duration of the saccade. Premotor command is addressed to the abducens neurons. Among these neurons, the adbucens motoneurons (AMN) contact the ipsilateral lateral rectus muscle, while the abducens internuclear neurons (AIN) are interneurons whose axons cross the median axis, follow the medial longitudinal fasciculus (MLF), and contact motoneurons of the contralateral medial rectus muscle. Though subtle differences exist (Fuchs et al., 1988), AMNs and AINs receive similar premotor commands (Fuchs et al., 1985). 

To be brief, on the neurophysiological level, one may find some arguments in favor of a conjugate saccade command in line with Hering’s hypothesis that a command of displacement in direction is commonly addressed to both eyes. To achieve a horizontal saccade to the right, the right premotor neuron similarly excites the right abducens motoneuron contracting the lateral rectus

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muscle in the right eye, and the right abducens internuclear neuron indirectly contracting the medial rectus muscle in the left eye (Figure 3A). There exist specific saccadic generators for rightward and leftward directions. The gate of this circuitry is achieved by the inhibitory control of the omnipause neural network.

Figure 3. (A) Model of binocular coordination following Hering’s hypothesis (classical descriptions). PPRF burst neurons produce a conjugate saccadic command; mesencephalic NR neurons produce pure vergence command. (B) Model of binocular coordination following Helmholtz’s hypothesis by King and Zhou. PPRF burst neurons are distinct for the left and right eyes. NR neurons produce on the one hand a position command of the monocular eye, on the other hand a fusional vergence command. AIN: abducens internuclear neuron; AMN: abducens motoneurons; BN: PPRF burst neuron (A) of saccade, and (B) of left and right eyes; LE: left eye; RE: right eye; MR: medial rectus motoneurons; NR: mesencephalic vergence neurons (near response); PPRF: paramedian pontine reticular formation. The median axis is shown in dotted line. Adapted from King and Zhou, 2000, Anatomical Record , issue 261, page 157, Figure 3, and page 159, Figure 6.

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2.2.2. Vergence Neurons If Hering’s hypothesis is true, there may be some neurons specifically involved in the control of vergence eye movements. Neurophysiological studies in monkeys have suggested that this might be the case. At the motor level, motoneurons of the medial rectus, located rostrally to the oculomotor nucleus, are organized in distinct subgroups innervating specific muscular fibers. Due to the fact that smaller fibers of the external layer of the medial rectus, probably involved in the generation of slow movements, correspond to a particular subgroup of motoneurons (subgroup C), it has been proposed that they may play a specific role in vergence eye movements (Büttner-Ennever et al., 1996). All oculomotor motoneurons and most abducens motoneurons discharge for both conjugate and disconjugate eye movements (Keller, 1973; Keller and Robinson, 1972; Mays, 1984). These motoneurons exhibit the same burst-tonic discharge pattern during vergence as during saccadic eye movements (Gamlin and Mays, 1992). But though most motoneurons serving medial and lateral rectus muscles convey saccade and vergence signals, different neurons may play a prominent role in either. At the premotor level, some neurons specifically involved in the control of vergence eye movements have been discovered in the mesencephalic reticular formation (MRF), in the dorsal and dorsolateral neighborhood of the oculomotor nucleus (Judge and Cumming, 1986; Mays, 1984; Mays et al., 1986). These neurons discharge in relationship to both step vergence in response to successively visible targets in depth (Mays et al., 1986) and smooth vergence in response to some target moving in depth (Judge and Cumming, 1986; Mays, 1984). Mays (1984) was the first to identify cells whose tonic activity is directly linked to convergence or accommodation angle. These tonic neurons discharge 10 to 30 ms before the start of the movement. Neurons associated to convergence have been found in much higher proportion than those associated to divergence: for that reason they are called near response neurons (NR). NR neurons discharge for both disparity and accommodation stimuli, which can be dissociated in visual stimulation, but some neurons remain prominently associated to disparity vergence (Judge

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and Cumming, 1986; Zhang et al., 1992). In the same mesencephalic area, burst neurons are also identified, whose discharge pattern is linearly correlated to the velocity of vergence eye movements (Mays et al., 1986). These vergence burst neurons resemble saccade burst neurons discharging in relationship to saccade velocity. As for vergence tonic neurons, there exist separate burst neurons for convergence and divergence, the former being once again more abundant than the latter. Finally, burst-tonic premotor neurons have also been identified dorsolaterally to the oculomotor nucleus, combining vergence velocity and position information in their output. The activity of vergence tonic neurons, burst neurons, and burst-tonic neurons in the mesencephalon is independent from conjugate movements of the eyes. To account for the dynamic interaction between saccade and vergence in combined eye movements, Zee et al. (1992) proposed that pause neurons, known to control through inhibition burst neurons for both horizontal and vertical saccades, also exert inhibitory control on vergence generators. In that way, the release of inhibition of these neurons common to saccade and vergence generators may be responsible for saccadevergence interaction – taking the form of vergence acceleration thanks to saccades and of saccade deceleration because of vergence. Such a prediction was supported a few years later by Mays and Gamlin (1995) who observed that the electric stimulation of pause neurons during vergence inhibits blink occurrence and slows down vergence, then by Busettini and Mays (1999) who reported that pause neurons cease to discharge during vergence eye movements. 

To be brief, consistent with the Hering hypothesis, there are some arguments at the neurophysiological level favoring a premotor command for vergence that might be independent from that of saccade. While burst neurons of the reticular formation (RF) may be the neural substrate of the saccade system (pontine RF for horizontal saccades, mesencephalic RF for vertical saccades), the mesencephalic supraoculomotor area (NR neurons) would be the neural correlate of the vergence system. Such saccade and

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vergence commands would be independently generated at the premotor level, then combined in extraocular motoneurons (Figure 3A). This is the traditional view adopted by many authors. I now introduce neurophysiological proposals following Helmholtz’s hypothesis.

3. NEUROPHYSIOGICAL ARGUMENTS AGAINST DISTINCT SACCADE AND VERGENCE SYTEMS 3.1. Premotor Neurons Despite much evidence for two distinct saccade and vergence systems, some neurophysiological findings suggest that the eyes may receive independent commands. McConville et al. (1994) have recorded in monkeys the activity of position vestibular pause neurons (PVP) within the medial vestibular nucleus (MVN) during conjugate but also disconjugate saccades. We previously mentioned that the MVN takes part in the saccade generator, participating in building up the position signal (Fuchs et al., 1985; Langer et al., 1986; Moschovakis et al., 1996; Scudder et al., 2002). Prior studies had shown that PVP neurons encode a conjugate or saccade position signal directly addressed to oculomotor neurons (III) (Scudder and Fuchs, 1992). However, these studies had only used as visual stimulation two targets at a far distance for eliciting conjugate saccades. The novelty of McConville et al.’s study (1994) was to elicit disconjugate saccades in response to target displacements in direction but also in depth. When monkeys were required to perform a disconjugate saccade between two targets aligned on the left eye, the authors showed PVP neuron discharge to be linearly proportional to the movement amplitude of the right eye performing the so-called monocular saccade. When visual stimulation called for conjugate saccades, the two eyes moved together with the same amplitude and, in this case, the activity of the same PVP neurons was directly linked to conjugate movement amplitude (as had been

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demonstrated by prior studies), which was consequently and by definition equivalent to the movement amplitude of the right eye. Therefore, PVP neurons appear to encode not a binocular but a monocular command. Recording up to twenty PVP neurons in the MVN, the authors showed that 50% of them discharge in relation to the ipsilateral eye whereas the remaining 50% discharge in relation to the contralateral eye. As the output of PVP neurons is directly addressed to oculomotor neurons (III), these observations are incompatible with the hypothesis of a conjugate premotor command. As emphasized by King and Zhou (2000), this result does not completely invalidate Hering’s hypothesis as PVP activity may reflect a sum of saccade and vergence signals built upstream. Therefore, a more decisive test of Hering’s hypothesis would be to measure the discharge of burst neurons of the paramedian pontine reticular formation (PPRF) expected to provide the conjugate or saccade command signal, but this time during disconjugate saccades. Zhou and King (1998) studied burst neurons of PPRF, taking advantage of the fact that the number of action potentials (AP) in their discharge is proportional to saccade amplitude. Should burst neurons encode a conjugate command, the number of emitted APs during a saccade ought to be correlated to the conjugate component of the eyes, which operationally corresponds to the average of the two eye positions. Alternately, should burst neurons encode a monocular command, the number of emitted APs ought to be linked to movement amplitude of either one or the other eye. Therein the saccade between two targets aligned on one eye (monocular saccade according to the authors’ terminology) is a privileged tool as the amplitude of the conjugate component differs from that of saccade amplitude done by the eye performing the movement: the former is one half of the latter. Such a difference in amplitude should be sufficient to detect without ambiguity the corresponding neural discharge pattern. Zhou and King (1998) trained three monkeys to perform three types of saccades: conjugate saccades, monocular saccades (targets aligned on one eye), and disconjugate saccades (in which the targets are not aligned with any of the eyes). When the monkey performed a conjugate saccade of 8 degrees, the burst neuron

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of PPRF emitted 8 APs on average. The discharge preceded by a few milliseconds the start of the saccade and its duration was equivalent to that of the saccade (30 ms). Based on this proof of evidence, many authors (e.g., Fuchs et al., 1985; Scudder et al., 2002) conclude that burst neurons convey a conjugate signal (for ipsilateral saccades). However, for a conjugate saccade, saccade amplitude by either one or the other eye is equal to that of the conjugate component (the average position of the eyes), which rules out any distinction between binocular and monocular commands. When the monkey performed a monocular saccade between two targets aligned on the left eye (the right eye moved by 8 degrees to the left whereas the left eye remained stationary), then the same burst neuron still emitted 8 APs on average and not 4 as the expected absolute value of conjugate component. The discharge duration was itself 60 ms instead of 30 ms, equivalent to the duration of the saccade performed by the right eye. This result suggested that the burst neuron encodes a monocular signal for the right eye. More convincing was the situation of the disconjugate saccade in which the left eye moved 8 degrees to the right and the right eye moved 6 degrees to the left. In such a case, the conjugate component was (8-6)/2 = +1 degree. In this situation, the same burst neuron did not emit 1 AP but 6 APs on average. The discharge duration was also equivalent to that of the combined eye movements. Zhou and King (1998) showed that among 98 burst neurons of the PPRF, 79% encode not a binocular but a monocular signal. 50% of them showed some preference for the right eye and 50% preferred the left eye; these neurons being mixed within the PPRF. The work of King and Zhou was confirmed and further extended by the laboratory of Cullen (Sylvestre et al., 2003; Van Horn and Cullen, 2008; Van Horn et al., 2008; Waitzman et al., 2008). Sylvestre et al. (2003) examined the role of burst-tonic neurons located in NPH and MVN (recall that these nuclei take part of premotor saccadic circuitry) in the generation of conjugate saccades, but also disconjugate or disjunctive saccades and fixation. They showed that these neurons carry both eye position and eye velocity-related signals during conjugate saccades. More interestingly, the authors also showed that during disconjugate saccades and fixation a

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majority of burst-tonic neurons of NHP and MVN preferentially encode the position and the velocity of a single eye, while a minority of them has conjugate sensitivities. Van Horn et al. (2008) tested whether the premotor command to generate disconjugate saccades originates in either saccadic or vergence centers. To achieve this goal, they trained two monkeys to perform conjugate saccades, disconjugate saccades, and smooth saccade-free vergence along the median axis, and recorded 74 saccadic burst neurons (SBNs) of the brain stem burst generator, 30 and 44 of which were respectively EBNs and IBNs, commonly assumed to drive the conjugate component of eye movements. They found that, during disconjugate saccades, SBNs carried substantial vergence-related information. Specifically, vergence velocity during disconjugate saccades was synchronized with the burst onset of EBNs and IBNs. Importantly, the majority of SBNs preferentially encoded the dynamics of an individual eye during disconjugate saccades. In another study, Van Horn and Cullen (2008) retested whether the saccadic premotor circuitry encodes not conjugate but rather monocular commands for one eye or the other during saccades. In three monkeys, they recorded 57 SBNs in the brainstem saccadic generator, 22 and 35 of which were respectively EBNs and IBNs, while the animals performed vertical saccades between near and far targets aligned in the median axis, thus requiring vergence but no horizontal saccade. Once again, the authors found that the majority of SBNs preferentially encoded the velocity of the ipsilateral eye. Taken together, these studies (Sylvestre, et al., 2003; Van Horn and Cullen, 2008; Van Horn et al., 2008) provide strong evidence that the premotor neuron commands from the brainstem saccadic circuitry are sufficient to ensure the shifts of gaze in 3D space. Waitzman et al. (2008) explored the role of central mesencephalic reticular formation (cMRF) in disconjugate saccades. Previously, the cMRF, located ventrally to the supraoculomotor area (SOA) and lateral to the oculomotor nucleus, was sought to encode only conjugate saccades. Once again, the authors evidenced from single unit recordings and electrical stimulation that cMRF neurons not only encode conjugate but

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also vergence-related information closely associated with the movement of an individual eye. Thus, similarly to the demonstration for the brainstem saccadic circuitry, these findings support the hypothesis that the mesencephalon also shapes the activity of premotor saccadic neurons by encoding both conjugate and vergence commands.

3.2. Motoneurons At the motoneuron level, King et al. (1994) and Zhou and King (1996, 1998) have examined the profile of discharge of abducens motoneurons (AMNs) during conjugate and disconjugate saccades. Once again, their discoveries disagree with traditional descriptions. Surprisingly, the authors have shown that most AMNs discharge in relationships to movements of the two eyes. Only a few cells are monocular and discharge in relationships to either the ipsilateral or contralateral eye. To characterize the ocular preference of AMN, Zhou and King (1996) used an ocular selectivity (OS) indicator varying from -1 to +1: values between 0 and +1 indicated some preference for the ipsilateral eye (+1 indicating exclusive monocular coding for the ipsilateral eye); values between -1 et 0 indicated some preference for the contralateral eye (-1 indicating exclusive monocular coding for the contralateral eye). Value 0 indicated binocular coding with any preference for one eye or the other. Among 136 examined AMNs, the majority of neurons exhibited a discharge related to both eyes, with some preference for the ipsilateral eye (positive OS). Only a minority of neurons exhibited an exclusive preference for one eye, which was almost ipsilateral. These data are surprising as abducens motoneurons innervate a single eye (the ipsilateral eye with respect to the abducens nucleus), yet most of them discharge even when the eye remains stationary. King and Zhou (2000) and Zhou and King (1996) suggested that AMN might encode not a monocular but a binocular command. However nature may even be more complex. As previously mentioned, motoneurons receive two commands: a velocity command (the burst discharge) and a position command (the tonic discharge). These two commands are supposed to be

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generated through different circuits and to combine in the abducens nucleus (Fuchs et al., 1985). Following this principle, abducens motoneurons (AMN) and abducens internuclear neurons (AIN) have a discharge component linked to eye velocity and another to eye position. By examining ocular selectivity of abducens neurons for eye velocity (OSV indicator) and for eye position (OSP indicator), Zhou and King (1996) observed that the OSV value of a neuron does not predict its OSP value, suggesting some independence of these indicators. However, most AMNs have positive OSV and OSP values, showing that neurons prefer the eye that is innervated (ipsilateral). For AINs, OSV value is preferentially negative, suggesting that these neurons convey the appropriate velocity signal in agreement with their projection to the motoneuron of contralateral medial rectus. An OSP value of AINs is itself divided between ipsilateral and contralateral eyes. King and Zhou (2000) proposed that during conjugate movements, AINs may convey the appropriate position command to the contralateral eye, but little influence on the motoneurons of medial rectus muscles during symmetrical vergence. Indeed, the AIN global discharge varies by little, as 50% of them increase their activity while the remaining 50% reduce it. More recently, King (2011) concluded that AINs convey primarily a position signal to medial rectus motoneurons to maintain gaze direction. The velocity command for any saccade (conjugate or disconjugate) is conveyed to the medial rectus by the burst generator including the monocular burst cells. Further, slow vergence corrects and maintains the required vergence position but does not play a role in producing gaze shifts in depth (King, 2011). These findings were extended by Cullen and colleagues (Sylvestre and Cullen, 2002; Van Horn and Cullen, 2009). Sylvestre and Cullen (2002) characterized the discharge dynamics of abducens nucleus neurons (ABN, including the two populations of AMNs and AINs) during horizontal disconjugate saccades. The authors showed that, during such unequal saccades, the majority of ABNs preferentially encode the velocity and the position of the ipsilateral eye, while the remaining neurons can encode the conjugate motion of the eyes. In other words, though ABNs can encode the

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motion of both eyes during disconjugate saccades, the activity of most ABNs is correlated to the movement of the ipsilateral eye. More recently, Van Horn and Cullen (2009) characterized the discharge dynamics of oculomotor neurons (OMNs) during disconjugate saccades in the horizontal plane. They showed that the majority of OMNs encode the position and velocity of the ipsilateral eye during disconjugate saccades. In a recent synopsis, Cullen and Van Horn (2011) proposed that the majority of premotor saccadic neurons dynamically encode the movement of a single eye, without the requirement of a separate vergence system, for gaze shifts in direction and in depth. On the other hand, while motoneurons (ABNs and OMNs) drive fast and slow vergence movements, the premotor saccadic neurons discharge only in relationship to fast vergence, suggesting distinct premotor pathways for controling fast and slow vergence, consistent with neuroanatomical evidence. Indeed, using retrograde transneuronal tracing with rabies virus in the lateral rectus muscle containing both fast and slow muscle fibers, Ugolini et al. (2006) showed distinct premotor connectivity for fast vs. slow MNs. For fast eye movements (saccades, vestibule-ocular reflex), the premotor connectivity involves the known circuitry for horizontal (PPRF, NPH, medRF, MVN) and vertical (Y group, interstitial nucleus of Cajal, riMLF) movements as well as cMRF. For slow eye movements (vergence and smooth pursuit), the premotor connectivity involves SOA, cMRF, and portions of NPH and MVN. Chen et al. (2011) examined in five internuclear ophthalmoparesis (INO) patients and five healthy volunteers the adducting/abducting peak velocity and acceleration ratios during gaze shifts between equidistant targets and between far and near targets aligned on the visual axis of one eye. While the initial component of each eye’s movement did not differ between the two conditions, INO patients did not adapt, as compared to controls, adducting velocity in response to viewing conditions, suggesting that horizontal saccades may be controlled by disconjugate signals preceded by an initial conjugate transient and followed by a slow vergence component.

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In short, the approach made by King and Zhou (King and Zhou, 2000; King et al., 1994; McConville et al., 1994; Zhou and King, 1996, 1998), Cullen’s team (Cullen and Van Horn, 2011; Sylvestre et al., 2003; Sylvestre and Cullen, 2002; Van Horn and Cullen, 2008, 2009; Van Horn et al., 2008; Waitzman et al., 2008), and Chen et al. (2011) is innovative. The authors contend that premotor neurons expected to encode binocular commands in fact encode a monocular signal, whereas motoneurons supposed to encode a monocular command in reality can encode a binocular signal (Figure 3B). Though it is more complex, such a conception sheds new light on binocular coordination underpinnings, which has been formalized in a model introduced by King and Zhou (see Section 4.2.2).

4. MODELS OF BINOCULAR COORDINATION 4.1. Neo-Heringian Models of Saccade-Vergence Generation Zee et al. (1992) introduced a series of models inspired from local feedback models to formalize premotor mechanisms in the generation of pure saccades, pure vergence, and combined saccade-vergence eye movements. They emphasize the inhibition function ensured by the omnipause neural network. To account for the facilitation of vergence by saccades in combined eye movements, Zee et al. (1992) proposed that the interaction between saccades and vergence acts at the premotor level, and not in the oculomotor plant as previously suggested by Ono et al. (Ono and Nakamizo, 1978; Ono et al., 1978) or Kenyon et al. (Kenyon and Stark, 1983; Kenyon et al., 1980a, b). Observing in particular that horizontal vergence is facilitated not only by horizontal saccades but also vertical ones, Zee et al. (1992) suggested that the omnipause neural network, exerting inhibitory control on generators of both horizontal and vertical saccades, may also exert similar control on vergence generators.

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Zee et al. (1992) proposed three models of vergence generation associated with saccades. The first model, so-called Saccade-related Vergence Burst Neuron (SVBN), exploits the hypothesis that there may be a separate set of premotor burst neurons of vergence associated with saccades. The second model, so-called Difference Burst (DB), advocates for separate burst neurons for right eye and left eye. The third model, socalled Multiply, interprets facilitation of vergence during saccades as the result of an increase in vergence velocity gain. The common denominator of the three is that omnidirectional pause neurons play a pivotal role in saccade-vergence interaction. The first and third models are in line with Hering’s hypothesis of distinct saccade and vergence systems, whereas the second model is an attempt to adhere to Helmholtz’ hypothesis of separate commands for the two eyes. For that reason, the latter will be presented later together with neo-Helmholtzian models.

Figure 4. Saccade-related vergence burst neurons (SVBN) model by Zee et al. In this model, there exist burst neurons separately for pure saccades (saccade burst neurons, SBN), for pure vergence (vergence velocity neurons, VVN) and for saccade-related vergence (SVBN). The outputs of SVBNs and VVNs are summed up to produce vergence velocity command (VVC). Omnidirectional pause neurons (OPN) inhibit SBNs and SVBNs while VVNs are inhibited by specific vergence pause neurons (not shown). CME: conjugate motor error; CVC: conjugate velocity command; LE: left eye; RE: right eye; VME: vergence motor error. From Zee et al., 1992, Journal of Neurophysiology, issue 68, page 1634, Figure 15A (© The American Physiological Society, with permission).

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Figure 5. Multiply model by Zee et al. In this model, there exist burst neurons separately for pure saccades (saccade burst neurons, SBN) and for pure vergence (vergence velocity neurons, VVN). Omnidirectional pause neurons (OPN) partially inhibit VVNs so that during a saccade, when OPN activity is released, VVN gain increases from 1.0 to K+1.0. VVNs are also inhibited by specific vergence pause neurons (not shown). Other notations as in Fig. 6 From Zee et al., 1992, Journal of Neurophysiology, issue 68, page 1634, Figure15D (© The American Physiological Society, with permission).

The SVBN model is shown in Figure 4. In this model, Zee et al. (1992) assumes separate burst neurons for pure saccades (SBN) and pure vergence (VVN), and an additional set of burst neurons for vergence when it is associated with saccades (SVBN). Omnidirectional pause neurons (OPN) exert inhibitory control on both the activity of saccade burst neurons (SBN) and that of vergence burst neurons associated with saccades (SVBN), whereas burst neurons of pure vergence (VVN) may be under the inhibitory control of specific pause neurons – VPN (not shown in the figure). SVBN generates premotor commands of horizontal vergence, but only during concomitant horizontal or vertical saccades. The output of the saccade-related vergence pathway (SVBN) is added to that of pure vergence (VVN) and, in this way, specifically enhances vergence velocity during saccades. In the Multiply model, Zee et al. (1992) assumes that facilitation of vergence by saccades in combined eye movements may be related to some specific nonlinear interaction expected to occur at the level of premotor neurons. The model is shown in Figure 5. In this model, there exist separate generators for pure saccades (SBN) and for pure vergence (VVN).

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Omnidirectional pause neurons (OPN) inhibit saccade generators (SBN), whereas vergence generators (VVN) are inhibited by specific pause neurons (VPN, not shown in the figure). However OPN might partially inhibit VVN, selectively during saccades, when vergence is associated with a saccade. To account for facilitation of vergence by saccade, nonlinear interaction in premotor structures can be tested by increasing the gain of pure vergence velocity neurons (VVN). Such an increase in the gain might be due to releasing inhibition of omnidirectional pause neurons necessary to saccade execution. 

In short, Zee et al. (1992) introduce two neo-Heringian models to account for saccade-vergence interaction, assuming the existence of separate generators for saccades on the one hand and vergence on the other, each having their own inhibitory system. In the Saccade-related Vergence Burst Neurons (SVBN) model, a supplementary class of vergence burst neurons may only act during saccades and may be under the inhibitory control of the omnidirectional pause neurons that prevent pure saccade. In the Multiply model, the omnipause neural network primarily acts on saccades and has an indirect influence on vergence burst neurons.

4.2. Neo-Helmholtzian Models 4.2.1. Difference Burst Models by Zee and Collaborators (1992) In the Difference Burst (DB) model, Zee et al. (1992) allowed themselves to assume the viewpoint of separate generators for each eye. In this view, there exist specific saccade burst neurons for the left eye and right eye. The DB model is shown in Figure 6. In this model, a conjugate motor error (CME) is addressed with the same sign to separate burst neurons of the right eye [BN(RE)] and the left eye [BN(LE)], and added to the vergence motor error (VME) signal, which is itself addressed to burst neurons of both eyes with opposite signs. Omnidirectional pause neurons (OPN) exert their inhibitory control on burst neurons of the two eyes. In

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this way, OPNs are capable of controlling the vergence command selectively during a saccade and thus facilitate vergence thanks to saccades. However, the DB failed to simulate experimental data accurately as the output of the saccade-related vergence pathway could not be modeled to interact correctly with the changes in horizontal alignment attributed to the saccades themselves. Thus, Zee et al. (1992) introduced a modified version in which they assumed the existence of a class of saccade burst neurons (SBN) in addition to saccade burst neurons of the right eye [BN(RE)] and the left eye [BN(LE)]. However, the addition of a second class of burst neurons did not make the modified DB model more flexible.

Figure 6. Difference burst (DB) model by Zee et al. In this model, there exists burst neurons separately for the left eye [BN(LE)] and right eye [BN(RE)]. The conjugate saccadic motor error (CME) and vergence motor error (VME) are summed up and sent to burst neurons with the same and opposite signs, respectively. Upstream, VME is multiplied by a gain GSV specific for convergence and divergence. The output of pure vergence velocity neurons (VVN) is multiplied by 0.5 and added to the outputs of BN(LE) and BN(RE). Omnidirectional pause neurons (OPN) inhibit BN(LE) and BN(RE), while VVNs are inhibited by specific vergence pause neurons (not shown). From Zee et al., 1992, Journal of Neurophysiology, issue 68, page 1634, Figure 15B (© The American Physiological Society, with permission).



The attempt by Zee, Fitzgibbon et Optican (1992) to model the saccade-vergence movement thanks to separate burst generators for the two eyes has failed. In the original Difference Burst (DB)

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4.2.2. Model by King and Zhou (2002) We have seen how King and Zhou provided neurophysiological arguments for monocular premotor commands for each eye. Their model is shown in Figure 7. This model differs from traditional models of saccade generation in three aspects: (i) burst generators are monocular; (ii) motoneurons receive binocular inputs; (iii) monocular neural integrators provide an input to near response (NR) neurons. To generate a saccade, burst generators use a local feedback model as those previously described. However, the motor error signal is supposed to be monocular. Thus, there are four burst neuron generators (BN) in King and Zhou’s model: one for each eye and one for right and left directions (King and Zhou, 2002). Let us for example consider burst generators of the right eye (with a white background in Figure 7). For rightward saccades, the output is connected to the neural integrator (NI) as an excitatory input; for leftward saccades, the output is connected as an inhibitory input. The omnipause neural network (OPN) exerts common inhibitory control on all burst generators. The response of burst neurons to the motor error signal is nonlinear. The shape of nonlinearity is similar to that used by Zee et al. (1992). Velocity, slide, and position signals are built up in the premotor circuitry of the brainstem. At this level, the circuitry is entirely monocular except for the omnipause neural network. In downstream stages, monocular signals are combined to produce a binocular innervation of the eyes. First, velocity, slide and position commands are added binocularly in the abducens nucleus. The authors suggest that abducens motoneurons

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Figure 7. Model of saccade generation based on monocular premotor commands by King and Zhou. In this model, there exist burst neurons (BN) separately for the left eye (LE) and right eye (RE). BN left: burst neuron for leftward direction; BN right: burst neuron for rightward direction; NI: neural integrator; Left/Right abducens: abducens neurons (VI); Left/Right MR: medial rectus neurons (III); NR: near response neurons; OPN: omnidirectional pause neurons. Adapted from King and Zhou, 2002, Annals of the New York Academy of Sciences , issue 956, Page 275, Figure 1.

(AMN) and abducens internuclear neurons (AIN) encode the same signal, though subtle differences exist. Indeed, AINs provide the binocular control command appropriate to motoneurons of contralateral medial rectus during conjugate eye movements. Such connections are in line with anatomical data. Secondly, King and Zhou (2002) assume that monocular position outputs of neural integrators are subtracted in the mesencephalic burst vergence neurons (NR) to generate the position signal of pure vergence. During disconjugate movements of the eyes, these neurons provide the vergence binocular innervation to motoneurons of medial rectus. These connections between neural integrators and mesencephalic vergence

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neurons are not anatomically established. With respect to velocity and slide commands, they would reach motoneurons not via vergence neurons (NR) but via abducens and internuclear pathways. 

The model by King and Zhou (2002) contrasts with traditional models in hypothesizing the existence of monocular premotor commands and encoding of binocular information in motoneurons. Such a hypothesis is based on neurophysiological findings by the same authors, and has been corroborated and extended by Cullen and colleagues (Cullen and Van Horn, 2011; Sylvestre et al., 2003; Sylvestre and Cullen, 2002; Van Horn and Cullen, 2008, 2009; Van Horn et al., 2008; Waitzman, et al., 2008). Otherwise, the model assumes the existence of a direct path between the neural integrator and mesencephalic vergence neurons (near response neurons, NR), which has hitherto not been anatomically confirmed. Similarly, the role of motor error signals in the production of the initial vergence remains hypothetical.

CONCLUSION A remarkable feature of human vision is that the two eyes are frontally placed on a horizontal line and separated by a few centimeters, implying that these two organs fully cooperate to allow for binocular vision. Following Hering’s seminal work, neo-Heringian psychophysicians have provided several arguments for separate conjugate and disconjugate systems, and neo-Heringian neurophysiologists have evidenced separate saccade and vergence commands at the premotor level, though the two systems may interact. In this context, conjugate and disconjugate systems are modular in their excitatory mechanisms (movement activation) but not in their inhibitory mechanism (movement suppression) common to both systems and causes their interaction. On the other hand, and in line with Helmholtz’s original proposal (Helmholtz, 1924-1925), one neoHelmholtzian psychophysician (Enright) has accumulated arguments for

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monocular programmed eye movements, while neo-Helmholtzian neurophysiologists (King and Zhou, Cullen’s team) have revealed monocular commands at the premotor level of oculomotor circuitry. To conclude, I suggest that both Hering and Helmholtz were right, as would be two blind contradictors describing from touch opposite parts of the same elephant (Turner, 1994). Saccades may be disconjugate and rapidly shift the line of sight in depth, a formulation largely consistent with Helmholtz’ view. However, there also exists a slow fusional vergence system that operates continuously to reduce ocular disparity by controling both eyes, as argued by Hering (Cullen and Van Horn, 2011; King, 2011).

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In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 7

THE BRAINSTEM AND ORAL FUNCTIONS: THE TRIGEMINAL SYSTEM IN HEAD POSTURE Catherine Strazielle1,2,3,* and Magali Hernandez2,3 1

Lorraine University, Department of Anatomy and Physiology Faculty of Odontology, Nancy, France 2 Lorraine University, Lab. “Stress, Immunity, Pathogens,” Vandoeuvre-les-Nancy, France 3 CHRU of Nancy, Vandoeuvre-les-Nancy, France

ABSTRACT At the level of brainstem, the central organization of head posture and movements is under the control of the vestibulo-spinal system with adjustments from somatosensory afferents and vision. The trigeminal system is most of the time excluded from this functional network whereas: 1) oral functions require a constant synergic contribution of both the mandible and head in postural control of a static position or dynamic action, 2) it is in charge of the extraocular muscle proprioception essential *

Corresponding Author Email: [email protected]. Tel: +33 (0)9 72 74 62 39.

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Catherine Strazielle and Magali Hernandez for gaze control and spatial orientation and, 3) facial stimulation triggers and influences a wide range of head movements. By studying the functional network of the multiple intermingled reflex activities generated in the brainstem by the involved nuclei, we will argue the relevance of the trigeminal system on the integration of postural control mechanisms supporting stable head position, balance, and movements.

1. INTRODUCTION One of the most important advances in the evolution of the head is the transformation of the first arch of the visceral skeleton into components of the jaws. In jawed fishes (gnathostomes), the trigeminal nerve, previously incorporated in part with the lateral line in association to the vestibular system for the equilibrium of the whole body, acquired new proprioceptive afferents to a novel central structure of the brainstem, the mesencephalic trigeminal nucleus (Butler and Hodos, 1996). This sensorimotor individualization procured for the trigeminal system more sophisticated oral functions, allowing animals to become more efficient predators. The terrestrial life modified the postural control of body and head position and movements against gravity as the acquisition of a neck contributed to spatial head orientation in relation to the environment. The bipedic posture of primates changed the craniofacial equilibrium with the face and its stomatognathic structures migrating from an anterior position in front of the cranial region to a new vertical position under it. This craniofacial architecture determined therefore a new balance between the anterior facial stomatognathic element animated by mandibular movements and a posterior cranial element animated by neck and head movements. Oral functions such as prey catching or prehension, chewing or grinding, grooming, speaking or even gnawing required a constantly combined mobilization of the mandible and perioral soft structures on one side in regard to the head position and movements on the other side. In contrast to the peripheral situation, when considering the central control of craniofacial motor activities, physiologists usually consider two separate systems: the trigeminal one in charge of sensorimotor functions controlling the mandibular movement and the vestibular one in charge of

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head position, spatial orientation, and head movements. Orthostatic and dynamic postural control of the head is mainly provided by vestibular nuclei and various specific and non-specific nuclei of the brainstem reticular formation that project to the cervical spinal cord. Their roles are to coordinate activities between pools of motor neurons, form networks of rhythmic neuronal activities for repetitive movements, and relay diverse peripheral and central information modulating motor output. The coordinated motor responses resulting from postural control of the craniofacial region reflect the “motor” link between trigeminal and vestibular systems. The “sensory” link and more precisely, the influence of the trigeminal system on vestibulo-oculo-spinal functions is less known, ignored by physiologists, uncertain or still controversial, especially when considering the effect of dental occlusion on head and body balance. However, rather than considering the two systems in parallel, would it not be relevant to consider them as a unique functional entity by integrating the trigeminal system into the vestibulo-oculo-spinal system? That is the question of this chapter. After a neuroanatomical presentation of the central nervous structures involved in postural control of the craniofacial region, we will study the trigeminal influence on vestibular function. We will base our discussion on the postural control at lower level of the brainstem, the executive level in charge of the reflex activities and motor adjustments for behavioral responses precisely adapted to the environment.

2. ANATOMICAL ORGANIZATION OF THE TRIGEMINAL NERVOUS SYSTEM 2.1. The Brainstem Trigeminal Nuclear Complex The trigeminal nerve conveys both exteroceptive and proprioceptive information from the face to the trigeminal nuclear complex of the brainstem (Darian-Smith, 1973; Waite and Tracey, 1995). Its innervation territories reflect the hypertrophied nuclear column extending throughout the brainstem, from the sensory cervical spinal cord to the superior part of

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the mesencephalon. The central axons of trigeminal ganglion cells distribute into the principal trigeminal nucleus and the three parts of the spinal trigeminal named pars oralis, interpolaris, and caudalis (Capra and Dessem, 1992). Except in the spinal trigeminal pars interpolaris, a welldefined cephalotopic organization was observed, ventrally for those of the ophthalmic division, intermediate for those of the maxillary division, and dorsally for those of the mandibular one (Capra and Dessem, 1992; Nord, 1967). In addition to its multiple intrinsic ascending and descending connections, primary and secondary trigeminal afferents project mainly to the reticular formation, particularly the dorsolateral ponto-medullar, as well as the thalamus, the cerebellum, the trigeminal motor nucleus and the spinal cord, and other cranial nerve nuclei (Hayashi et al., 1984; Jacquin et al., 1982; Marfurt, 1981; for review Waite and Tracey, 1995; Walberg et al., 1985). Above the principal nucleus, the mesencephalic trigeminal nucleus is a long stream of large round neurons clustered in its caudal pontine part adjacent to the locus coeruleus (Rokx et al., 1986) and scattered along the border of the mesencephalic periacqueducal grey matter in its rostral part. Considered as an important relay of trigeminal proprioception, its functional organization will be related in detail in the next section. The trigeminal nerve provides the motor innervation for the jaw muscles. The trigeminal motor nucleus lies in a medial position of the principal nucleus. In the rat, it is usually divided into a large laterodorsal division for jaw-closing motor neurons and a smaller ventromedial division for motor neurons of jaw-opening muscles (Jacquin et al., 1983; Rokx et al., 1986). It is doubled with two satellite nuclei, the motor accessory and the intertrigeminal ones, involved in the motor innervation of oral and auditory regions (Meessen and Olszewski, 1949). Retrograde axonal tracing studies showed a large distribution of labeled fiber terminals in the trigeminal motor nucleus from premotor neurons located in parabrachial, supratrigeminal, and intertrigeminal regions, in the dorsal part of the principal and spinal (oralis and interpolaris pars) trigeminal nuclei, and in different rostral and caudal portions of the medullary reticular formation, more especially the parvicellular reticular one (Fay and Norgren, 1997;

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Inoue et al., 2002; Li et al., 1995; McDavid et al., 2006; Takamatsu et al., 2005). It is of interest to note that all the somesthetic information of the head converge into the trigeminal sensory nuclear complex, whereas the trigeminal motor output to jaw muscles diffuse also to all the other motor nuclei of the face through relays with reticular formation interneurons and the medial longitudinal tract. The interconnected network serves, at a lower level, to coordinate the activities in related motor nuclei and provide complex oral tasks such as, for example, moving the tongue or cheek beside the teeth to avoid biting when the jaw is closing or coordinating eye with jaw muscles in feeding behaviors, especially in predatory animals.

2.2. The Trigeminal Proprioception 2.2.1. The Oral Proprioception The trigeminal system is in charge of facial proprioception arising from receptors in jaw muscles and temporo-mandibular joints as well as skin and periodontal mechanoreceptors of the stomatognathic apparatus involved in the position and movement of the mandible. Proprioceptive fibers, mainly conveyed by the trigeminal mandibular branch, use at least two pathways (Figure 1). The first one is the mesencephalic pathway for jaw-closing spindles and periodontal mechanoreceptors, with cell bodies seen inside the mesencephalic trigeminal nucleus. Matesz (1981) found additional non-proprioceptive afferents from different types. Moreover, projections of afferents linked with intrapulpar mecanoreceptors were suggested (Yoshino et al., 1989). The second pathway relays proprioceptive information in the spinal trigeminal nucleus with cell bodies located in the trigeminal ganglion, for the Golgi tendon receptors, the mandibular joint receptors, and a number of periodontal mechanoreceptors (Figure 1). These two systems seem both to convey proprioceptive fibers for the conscious and unconscious pathways, since a trigeminal mesencephalic projection to the thalamus was demonstrated in the monkey (Luo and Dessem, 1995).

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Figure 1. Schematic distribution of trigeminal proprioceptive afferents and their central projections to the trigeminal sensory nuclear complex in the brainstem. The trigeminal mesencephalic and spinal oralis and interpolaris nuclei are the main targets of proprioceptive afferents. The information from temporo-mandibular joint (TMJ) receptors and jaw muscle spindles project exclusively on the respective trigeminal spinal and trigeminal mesencephalic nuclei, while those from extraocular and periodontal receptors are shared between the two brainstem sites. Exteroceptive information from oral mucosa receptors project on all ponto-medullary nuclei of the trigeminal sensory nuclear complex. The fibers projecting to the trigeminal principal nucleus constitute the ascending trigemino-thalamic pathway for conscious proprioception. (Major projections are in bold).

2.2.2. The Extraocular Muscle Proprioception In addition to oral proprioception, the trigeminal nerve conveys proprioceptive afferents from extraocular muscles (Figure 1). Localization of their cell bodies and central terminal projections was examined in different animals and results remain a matter of controversy, possibly in regard to variations between animal species. In the cat, intramuscular tracer

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injection displayed labeled cell bodies in the trigeminal ganglion and central fiber terminals in the spinal trigeminal interpolaris subnucleus (Buisseret-Delmas and Buisseret, 1990; Porter and Donaldson, 1991), as previously observed in the monkey (Porter, 1986). Ogasawara and colleagues (1987) found similar results in the cat but with the highest fiber terminal labeling in the oralis subnucleus. In some experiments, additional labeling was observed in the mesencephalic trigeminal nucleus (AlvaradoMallart et al., 1975), involving neurons with central vestibular projections (Buisseret-Delmas et al., 1990). Work in monkeys (Wang and May, 2008) corroborated the dual pathway of extraocular muscle proprioception. As different types of proprioceptive sensors have been described in these muscles (Büttner-Ennever et al., 2006), some authors suggested that the trigeminal spinal pathway with involvement of trigeminal ganglionic cells conveys information from non-spindle sensors, while the trigeminal mesencephalic pathway carries afferent fibers related to the small number of muscle spindles (Billig et al., 1997; Maier, 2000). 2.2.3. The Mesencephalic Trigeminal Nucleus The presence of primary afferent cell bodies inside the brainstem mesencephalic trigeminal nucleus is one of the most unusual organizations of any sensory system. However, it cannot be simply considered as a “proprioceptive ganglion” (Gregg and Dixon, 1973) in an ectopic position in the central nervous system because of different morphological and functional features (Lazarov, 2007). In the first place, the nucleus is composed of large pseudo-unipolar but also multipolar cells (Nomura et Mizuno, 1985; Shigenaga et al., 1988b; Walberg, 1984) attesting to primary and secondary neurons. In the second place, mesencephalic trigeminal neurons are rich in synapses: they receive axo-somatic and axodendritic synaptic inputs from the other nuclei of the sensory trigeminal nuclear complex and also from various brain regions involved in homeostatic functions, among those (for a review see Waite and Tracey, 1995) the reticular formation, hypothalamus (Copray et al., 1990; Nagy et al., 1986), cerebellum (Marfurt and Rajchert, 1991; Strazielle et al., 1994), tectum (Ndiaye et al., 2000), dorsal raphe (Copray et al., 1991), substantia

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nigra and ventral tegmental area (Copray et al., 1990), locus coeruleus (Takahashi et al., 2010), and amygdala (Shirasu et al., 2011), all of them susceptible to modulate the excitability of the cells. In the third place, the clustered neurons establish “zona adherens” contacts between them, equivalent to functional electrotonic coupling possibly for increasing information toward the motor nucleus or synchronizing cellular activities inside the nucleus (Curti et al., 2012; Hinrichsen and Larramendi, 1968; Xing and Yang, 2014). Finally, the neurochemical features of its innervation lead one to consider the nucleus as an integrating center involved in control reflex circuitries of oral functions (Lazarov, 2007). The jaw muscle spindle afferent cells are known to provide excitatory inputs and large inhibitory inputs via supratrigeminal interneurons (Fujio et al., 2016) and other nuclei of the adjacent reticular formation (Luo et al., 2001) onto the trigeminal motor neurons. Considered as a functional entity, this pathway is the anatomical substrate for the jaw stretch reflex. These primary mesencephalic trigeminal cells may also coordinate the activities of orofacial motor nuclei (trigeminal, facial, hypoglossal, and ambiguous nuclei) through direct projections to their motor neurons (Zhang et al., 2001) or projections to common populations of premotor neurons located in parvicellular and dorsal medullary nuclei of the reticular formation (Zhang et al., 2012).

2.3. Functional Organization of the Head Posture Among different levels in the motor control hierarchy, the brainstem is involved in the execution for both static and dynamic activities. One of the major elements of this executive level is postural control. It implies on one side head and body equilibrium to maintain a stable stance at rest and, on the other side, body adjustments throughout the movement (Lalonde and Strazielle, 2007). The so-called “medial postural system” described by Baker (1999) is formed with the vestibular system and reticular formation in association with descending vestibulo-spinal and medial reticulo-spinal tracts; it constitutes a functional network of particular importance in the

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control of posture and reflex behaviors (Lalonde and Strazielle, 2007). The additional eye movements contribute to the equilibrium of the body by gaze stabilization during head movements. The vestibular part of the inner ear is a full proprioceptive apparatus, giving the sense of head position and movement. It is concerned with spatial orientation, maintenance of equilibrium, and modification of muscle tone. The semicircular canals along with the ampulla detect rotational acceleration of the head (kinetic equilibrium) while the otolithic organs of the macula in utricule and saccule collect information on linear acceleration and static equilibrium of the head. Central projections of the vestibular ganglion terminate with regional specificities in all four vestibular nuclei, namely superior, medial (dorsal), inferior (descending), and ventral portion of the lateral (Deiter’s) as well as in the interstitial nucleus, a collection of cells between entering vestibular root fibers. Additional projections are observed to the accessory cuneate nucleus, portions of the reticular formation, particularly the lateral one as well as to the cerebellum (Carleton and Carpenter, 1984). Vestibular nuclei convey head motion signals to many brain regions. In short, the medial and lateral vestibulo-spinal tracts, arising respectively from medial-inferior and lateral nuclei, provide direct vestibular influence on the spinal cord (Baker, 1999; Donevan et al., 1990). Neurons in the superior and medial vestibular nuclei mediate vestibulo-ocular reflexes. The medial vestibular nucleus also sends projections to brainstem autonomic nuclei and the parabrachial nucleus, which integrates viscerosensory signals and has bidirectional connections with the amygdala. The ponto-medullary reticular formation plays an integrative role in the postural control system. When a perturbation occurs during the movement, by means of negative feedback reflexes, visual, vestibular, and somatosensory receptors produced information to the system for a rapid correction of unexpected disturbances (Lalonde and Strazielle, 2007; Lawrence and Kuypers, 1968). Most sensory afferents produce these reflex effects through interneuronal circuits. The medullary dorsal and parvicellular nuclei are particularly involved in the afferent part of the network, in relaying sensory inputs that may modulate motor output.

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Medial regions of the reticular formation (gigantocellular reticular nucleus of the medulla and nucleus reticularis pontis caudalis) produce the efferent part of the network by modulating signals via both dorsorostral facilitator and caudal inhibitory zones. They give rise to the medullary reticulospinal tracts, which mostly terminate on the ventral horn of the cervical spinal cord (Carpenter, 1991; Torvik and Brodal, 1957). The vestibulo-ocular reflexes produce compensatory eye movements in response to head displacements. Although extraocular muscles contain muscle spindles, eye proprioception seems to come mainly from palisade endings on the eye muscle tendons (Billig et al., 1997; Maier, 2000). It is distributed via the trigeminal nucleus to many key structures in the oculomotor system including the vestibular nuclei, cerebellum, and superior colliculus. The neural integrator for eye movements is accomplished by neurons in medial and superior vestibular nuclei and two other brainstem nuclei, the nucleus prepositus hypoglossi for the horizontal component and the interstitial nucleus for the vertical component in association with the vestibulo-cerebellum and the paramedian pontine reticular formation (Cannon and Robinson, 1987). The output signals arise from motor neurons localized in oculomotor, trochlear, and abducens nuclei of respectively the third (III), fourth (IV), and sixth (VI) cranial nerves. The medial longitudinal fasciculus is a complex bundle formed by ascending and descending fibers derived from various brainstem nuclei. It is the most important pathway for the brainstem postural control. The reticular formation largely contributes the descending fibers to the cervical spinal cord. The vestibular nuclear complex is also a main producer of fibers, arising mainly from medial and inferior nuclei for descending pathways to the spinal cord and also from medial and superior nuclei for the ascending pathways to the extraocular motor nuclei. Besides these long bundles, the medial longitudinal fasciculus forms a complex network of interconnected fibers between all the motor nuclei of the cranial nerves those involved in eye-and-head and oral reflexes - as well as sensory trigeminal and cochlear nuclei.

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3. THE TRIGEMINAL SYSTEM IN POSTURAL CONTROL OF HEAD AND NECK REGION 3.1. Postural Control of the Mandible The particularity of the mandible is its suspension and therefore submitted to the effects of gravity. Nevertheless, when a person is sitting or standing, the mandible, instead of falling down, remains in a relatively stable position characterized by its vertical dimension independent of dental occlusion, since an approximate distance of 2 mm is measured between the posterior teeth. This position is named the “rest” position, or rather “habitual position of the mandible,” a term more appropriate for a physiological active statement, according to Woda et al. (2001). The physiological mechanisms controlling the habitual position of the mandible are still controversial. Previous studies demonstrated the role played by the passive viscoelastic forces displayed by muscles, joint capsules, ligaments, and adjacent soft tissue (Yemm and Nordstrom, 1974) and authors presently agree as to their major role in static equilibrium of the mandible (Miles, 2007; Woda et al., 2001). Besides this passive phenomenon, repetitive jaw stretch reflexes could be another functional substrate by activating muscle spindles during consecutive downmovements of the mandible (Møller, 1976). Electromyographic activities in the jaw rest posture were sometimes denied by oral physiologists because they were very weak and difficult to record and possibly biased by experimental conditions (see Woda et al., 2001 for a review). However, Woda and colleagues (2001) argue for an additional jaw-closing muscle contractile activity in maintenance of the mandibular habitual position, an activity elaborated by spindle-mediated reflexes and probably by central motor programs. Physiologists reported the existence of a central body schema serving as a referential position in the central programs of postural motor control (Deetjen and Speckmann, 1994; Massion et al., 1998) and mandibular position may certainly be controlled in a similar fashion. Recently, continuous jaw oscillations were recorded on the mandible of

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human subjects sitting upright at rest and electromyographic experiments permitted us to conclude that this weak oscillatory activity of small amplitude reflects alternate jaw-opening and jaw–closing muscular activities arising from a central pattern generator, not a reflex servo-control mechanism which only activates jaw-closing muscles, the only ones to have muscle spindles (Jaberzadeh et al., 2003; Junge et al., 1998; Miles et al., 2004). Thus, the latter results denied a stretch reflex involvement in maintaining the mandibular resting position (Miles, 2007). The functional relation between mandible posture and head position is well known. Several clinical studies investigated this relation by recording the respective tonic activity of jaw muscles in regard to different head positions (Lund et al., 1970). Electric activities of temporal and digastric muscles were maximal in an orthostatic position of the head in the axis of the body. This tonic activity decreased when trunk and head were tilted backwards 45° when tonic activity of the lateral pterygoid muscle was maximal. Activities were minimal in the three muscles when the subject was in a horizontal position. According to the authors, the results would have been different had the head moved relative to the trunk (Lund et al., 1970) because of changes in proprioceptive receptors of the neck muscles. In the bilarynthectomized rat, it was shown that only preservation of neck afferents stimulated activities of temporal, masseter, and digastric muscles in cephalic dorsal flexion, while a ventral flexion of the head inhibited the electric activity of the same muscles (Funakoshi and Amano, 1973). Similarly, Zafar et al. (2000) demonstrated in humans a strong correlation between flexion-extension cephalic movements and vertical up-and-down movements of the mandible. The head position variations could influence the mandible at different levels of control: (1) at the periphery by inducing new strains on tissue and altering the viscoelastic forces in the muscles and adjacent oral soft tissues; (2) centrally by proprioceptive information collected in the vestibular organ, cervical muscles, and joints for modulating the trigeminal motor neurons by means of polysynaptic pathways through the reticular formation. Stabilization of the mandible occurs in a great number of situations. It has been shown that small up-and-down movements of the mandible are

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associated with head movements during locomotion (Flavel et al., 2003) and jaw stretch reflexes would be expected to counter this phenomenon and stabilize the mandible. As demonstrated previously in static work (Miles et al., 2004), an absence of electromyographic activity in jawclosing muscles was observed when walking was slow with a speed inferior to 0.7 m/s, attesting to the efficiency of soft tissue viscoelasticity in locomotion (Miles et al., 2003). However, bursts of electromyographic activity appeared in jaw-closing muscles with every step, increased in adequacy with walking or running speed and amplitude of the vertical movement of the mandible to a threshold (for a speed near 2m/s), and then leveled off or even decreased (Miles, 2007). The response latency of muscle activity was consistent with those of a monosynaptic stretch reflex, able to limit up-an-down movements of the mandible within a very small range of amplitude (Miles, 2007). Conversely, head and neck movements are undissociable from oral activities (Häggman-Henrikson et al., 2006). Head extension and flexion were observed respectively with jaw opening and closing (Zafar et al., 2000) and head movements synchronized with mandibular movements have been observed during chewing (Erickson et al., 2000). Findings of synergic mandibular and head-neck movements in both single and rhythmic vertical jaw activities suggested that coordinated mandibular and cervical movements are governed by pre-programmed central commands (Ericksson et al., 2000; Torisu et al., 2001).

3.2. Functional Organization between Trigeminal and Vestibular Systems Proprioceptive sensation of the cranio-facial region is supported by vestibular and trigeminal systems. For modulating eye and head movements and controlling balance and postural responses of the body, the vestibular nuclear complex not only encodes vestibular afferents but also visual and neck proprioceptive information for a better control of neck and eye muscles in both static and phasic positioning of the head. Since the

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trigeminal system is in charge of the oro-facial proprioception originating from structures involved in jaw postural function and susceptible to modify the cephalic equilibrium, the projection of trigeminal afferents on the vestibular nuclei as well the vestibular interaction with jaw muscles should be considered as a fact. Numerous neuroanatomical and electrophysiological studies demonstrated the functional relationships between vestibular and trigeminal systems. 3.2.1. Vestibular Influence on the Trigeminal System By nerve stimulation, Tolu and colleagues (Tolu and Pugliatti, 1993; Tolu et al., 1994) demonstrated the influence of the vestibular system on tonic activity of masseteric motor neurons - with a bilateral excitation but more efficient in the contralateral muscle - for the purpose of maintaining the jaw in a static position against gravity. The vestibular influence was also present in dynamic situation as vestibular macula stimulations modified the fiber length of both masseter muscles in relation to the spatial displacement of the head. In the same experimental conditions, excitatory responses were observed in digastric motor neurons as well, but with response latencies shorter in jaw-closing muscles than in jaw-opening ones and shorter in contralateral muscles than ipsilateral ones when considering the side of macular stimulation (Tolu et al., 1996). The motor response latencies argued in favor of polysynaptic reflex pathways. Tonic and phasic responses were similarly recorded in cervical muscles (Tolu and Pugliatti, 1993) attesting therefore to the integration of masticatory muscles with other antigravity head and body muscles under control of the vestibular system. Such vestibular modulation could also be observed on human jaw muscles. A stimulation of vestibular ampulla receptors by body rotation induced a higher excitability of masseteric motor neurons, still persistent during the next 5 min post-rotation phase (Hickenbottom et al., 1985). Deriu et al. (2000) described bilateral asymmetrical excitatory responses of masseteric motor neurons provoked by vestibular macular stimulation, as previously found in animals (Tolu and Pugliatti, 1993). Inhibitory masseteric reflex responses of short duration and latencies were

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also reported with transmastoid electrical vestibular stimulation (Deriu et al., 2003). Neuroanatomical studies support the physiological results. They revealed multiple vestibulo-trigeminal pathways. A direct contact between vestibular fibers originated from the parvicellular medial vestibular and caudal prepositus hypoglossi nuclei on one side, and bilateral masseteric motor neurons on the other side, was observed in rats (Cuccurazzu et al., 2007) and frogs (Matesz et al., 2008). Additional vestibular projections to the ponto-medullary reticular formation, trigeminal mesencephalic, and trigeminal spinal nuclei suggested polysynaptic connections (Cuccurazzu et al., 2007, Matesz et al., 2008; Valla et al., 2003). Transneuronal transport of pseudorabies virus provided evidence of long multisynaptic pathways (Giaconi et al., 2006). Virus injection in the rat masseter muscles produced infected neurons bilaterally in all vestibular nuclei with highest concentrations in inferior vestibular and caudal parts of medial vestibular and prepositus hypoglossi nuclei. Tracer injection in the vestibular nuclear complex also labeled cells in trigeminal sensory nuclei (Buisseret-Delmas et al., 1999; Giaconi et al., 2006; Lovick and Wolstencroft, 1983; Walberg et al., 1985) and adjacent subnuclei rich in premotor interneurons, as well as numerous subdivisions of the ponto-medullary reticular formation, more specifically the lateral, gigantocellular, intermediate, and parvicellular ones (Giaconi et al., 2006), all structures known to project largely to trigeminal motor neurons (Li et al., 1996; McDavid et al., 2006). At a longer survival time, infected cells appeared in the interstitial nucleus of the medial longitudinal fasciculus known for its vestibular inputs. Projections from both inferior and medial vestibular nuclei were found in the dorsal horn of the spinal cord and central cervical nucleus (Donevan et al., 1990). A double retrograde tracer technique combined with immunohistochemical labeling in these vestibular nuclei provided evidence of vestibular neurons projecting gamma-aminobutyric acid (GABA) -ergic axonal inputs to both cervical spinal cord and trigeminal sensory nuclei (Blessing et al., 1987; Valla et al., 2003). The vestibular system may therefore assure a concomitant modulation of sensory information delivered by the neck and the face.

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The present findings suggest that the vestibulo-trigeminal relationship is quite complex, employing multiple pathways to connect the vestibular system with the trigeminal sensory-motor nuclei. As the vestibular apparatus was demonstrated to exert two short- and long-lasting responses on limb muscles (Britton et al., 1993), similar vestibular actions may occur in masseter. The multisynaptic vestibulo-trigeminal pathways may constitute the anatomical support of the needful tone adjustments of the masticatory muscles in opposition to gravity during all head movements or position changes. Occurring permanently in various oro-facial motor functions, they would require long-lasting tonic inputs from the vestibular system (Deriu et al., 2010). The short-latency pathways, allowing rapid phasic vestibular inputs to jaw muscle function, may be efficient for rapid jaw adjustments in relation to brisk head movements. They may serve in feeding behavior for fine jaw readjustment in prey attack and prehension when the head is moving. These two sets of vestibulo-masseteric responses may also participate in the control of vertical jaw movements reported in locomotion with amplitudes depending on up-and-down head movements and the nature of gait (Miles et al., 2004; Miles, 2007). 3.2.2. Role of the Trigeminal Projections on Vestibular System Several studies by Petrosini, Troiani and colleagues (Petrosini and Troiani, 1979; Petrosini et al., 1979; Troiani and Petrosini, 1981; Troiani et al., 1981), attest to a trigeminal role on the vestibular system controlling head posture and orientation.

1) Electrical or mechanical stimulation of trigeminal sensory afferents in the guinea pig modulated positively or negatively the discharge rate of spontaneous activity and also rhythmic activity of vestibular neurons receiving primary inputs from labyrinthine stimulation (Troiani and Petrosini, 1981); when compared with neuronal responses produced by labyrinthine stimulation, the trigeminal effects were shorter in duration and weaker in intensity but with a convergence of all information from the face on the same vestibular units; the latency values of evoked potentials were

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variable from 1.2 to 6.2 ms, indicating either direct trigeminovestibular projections or polysynaptic pathways by the reticular formation (Marfurt and Rajchert, 1991; Pfaller and Arvidsson, 1988; Torvik, 1956) or cerebellum (Marfurt and Rajchert, 1991), although trigeminal modulation of vestibular neurons were still exerted in cerebellectomized animals. According to the authors, these trigemino-vestibular inferences may serve, through vestibulo-spinal pathways, to the calibration of all reflex head movements that act in combat situations and feeding. The variation of neuronal rhythmic activity may also indicate the possible regulation of a vestibular nystagmus provoked by ocular mobility. In a recent clinical study (Park et al., 2014), mastication induced imbalance and nystagmus in two patients with a prior history of acute vestibulopathy; mastication may also modulate nystagmus in patients with both peripheral and central vestibulopathies. As when electrical stimulation of the trigeminal nerve modulates spontaneous activity of vestibular neurons in guinea pigs (Troiani and Petrosini, 1981), trigeminal sensory-motor information generated by the chewing action may modulate the vestibular system, asymmetrically when it is unilaterally injured. Moreover, according to Park et al. (2014), chewing-induced vibrations transmitted to the labyrinth via the jaw bones may be a source of nystagmus when the functioning is unequal between the two vestibular organs on account of unilateral pathologies. 2) Unilateral section of the right trigeminal nerve in a guinea pig previously hemi-labyrinthectomized on the right induced the reappearance of all symptoms characterizing a postural asymmetry: head and trunk torsion to the right, extension of left forelimb, and impairment of body and head righting reflexes from lateral decubitus; eye nystagmus to the left, and circling or rolling movements to the right were also temporally present but disappeared in the hours following the neurotomy (Petrosini and Troiani, 1979). Visual information and spinal sensory afferents are known to be important for compensating a vestibular input defect

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Catherine Strazielle and Magali Hernandez (Bronstein and Guerraz, 1999; Fox, 1990; Sadeghi et al., 2011; Schaefer and Meyer, 1973). The Petrosini and Troiani (1979) study indicated that trigeminal afferents might also palliate the deficit of vestibular information. An electrophysiological study of vestibular nuclei on both injured and intact sides suggested a direct action of the trigeminal afferents on vestibular compensation (Petrosini et al., 1979). The trigeminal system may lead to a new functional balance between the two sides by an inhibitory action on the hyperactive vestibular nuclei of the intact side and a consequent decrease of the inhibitory tonic influences on the deafferented nuclei. Thus, evidence is provided that the trigeminal system plays a role on the mechanism of vestibular compensation. However, the trigeminal section performed in the Petrosini and Troiani (1979) study was total and we cannot conclude in favor of which specific afferents trigger compensatory behaviors. In addition to direct projections to the vestibular nuclear complex, trigeminal afferents could also be mediated by cerebellar pathways, since the cerebellum plays a crucial role in the consolidation of vestibular compensation (Beraneck et al., 2008; Dutia, 2010). 3) Another function in body posture and orientation is the righting reflexes exerted mainly by the vestibular apparatus and the somatosensory system and adjusted by visual and neck proprioceptive information for a normal head and body erect position. In the study by Petrosini and Troiani (1979), reappearance of impaired righting reflexes after trigeminal neurotomy in vestibular compensated animals suggested a trigeminal contribution to righting function. To study the trigeminal role on the head righting reflex, Troiani et al. (1981) abolished body righting reflexes by restraining the animals in a body-holder tube. Results showed that the head righting degree of normal animals reached a mean value of 71°, which decreased by 25% on the side of the trigeminal nerve section. In bilateral labyrinthectomized animals, despite a rectilinear head-body axis

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and the absence of nystagmus, head righting degree fell 80% to a value of 13.5°, completely abolished on the side of the trigeminal nerve section while a partial head righting could still be elicited when the animal was laid on the contralateral side of the trigeminal neurotomy. Similar effects were obtained when the animals were blindfolded, indicating no contribution of the optical righting reflex. These results recognized the existence of a trigeminal headrighting reflex. Like the other sensory afferents, trigeminal ones derived from the face provide additional information to vestibular neurons and neck motor neurons for a better head adjustment. According to Troiani et al. (1981), the trigeminal system contributes to the dynamic phase of righting function while head maintenance in its static erect position is mainly exerted by otolithic input and vestibular function (Graybiel, 1974). Recently, a rat study evaluated dynamic cerebral plasticity by means of brain glucose metabolism during vestibular compensation after unilateral labyrinthectomy performed by surgical or chemical procedures (Zwergal et al., 2016). Among the regional metabolic alterations observed throughout the brain, the vestibulo-cerebellum and spinal trigeminal nucleus were activated on the same side as the labyrinthine lesion, 2-9 days after surgical and 7-9 days after chemical unilateral labyrinthectomy, such results bringing another proof of a trigeminal contribution to vestibular function. Sadeghi et al. (2011) showed that neck proprioceptive signals support vestibular neuronal activity in the first week post-unilateral labyrinthectomy. According to the authors and to the previous studies by Petrosini and Troiani (1979), trigeminal proprioceptive afferents from the face may likewise stimulate vestibular neurons (Sato et al., 1997) to palliate the labyrinthine information for a correct head postural orientation. Metabolic up-regulation was not reported in the mesencephalic trigeminal nucleus, possibly because of the limited resolution of the µPET technique in regard to a nucleus constituted with scattered cells. However, such a possible activation should not be ignored.

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Neuroanatomical investigations provided evidence of trigeminal sensory projections to the vestibular nuclear complex. After wheat germ agglutinin – horseradish peroxidase (WGA-HRP) infusion into three specific zones of the rat trigeminal ganglion, a modest amount of terminal labeling was observed in the ipsilateral superior and lateral vestibular nuclei, predominantly of mandibular origin according to the ganglionic zone injected (Marfurt and Rajchert, 1991). These direct primary trigemino-vestibular projections were previously reported (Matesz, 1981; Pfaller and Arvidsson, 1988; Torvik, 1956) or denied (Jacquin et al., 1983), probably in account of the different tracer (HRP) technique used. Direct primary trigeminal projections, with soma localized in the mesencephalic trigeminal nucleus and conveying proprioceptive information from the extraocular muscles, were labeled in the medial vestibular nucleus (Buisseret-Delmas et al., 1990). A later study showed projections from neurons in the caudal part of the mesencephalic trigeminal nucleus mainly to medial, inferior, and lateral vestibular nuclei and moderately to the peripheral part of the superior vestibular nucleus (Pinganaud et al., 1999). Secondary trigeminal afferents project more largely to the vestibular nuclear complex. Tracer injections in principal and spinal trigeminal nuclei labeled terminal fibers, predominantly in ipsilateral vestibular nuclei, with highest densities in the inferior (lateroventral part), medial (lateral part), and lateral (ventral part) ones (Buisseret-Delmas et al., 1999), the same targets as cervical spino-vestibular projections (Bankoul and Neuhuber, 1992; Matsushita et al., 1995). Injection of retrograde tracer in vestibular nuclei localized more precisely the trigeminal neurons involved in these trigemino-vestibular pathways (Diagne et al., 2006). They implied two neuronal populations, one localized in the ventral part of the trigeminal nuclear column receiving information from the ophthalmic branch territory (Waite and Tracey, 1995) and a dorsal one receiving sensory and proprioceptive information from the mandibular branch of the trigeminal nerve (Waite and Tracey, 1995). The latter neurons did not project to the lateral vestibular nucleus (Diagne et al., 2006). These results suggest a role of the oral somatosensory and stomatognathic proprioceptive information

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as pertinent as those of extraocular proprioception in control exerted by the vestibular nuclei on head posture and movements.

3.3. The Trigeminal System in Gaze Control and Head Posture We have seen that the trigeminal system establishes interconnections with the vestibular system. In a similar manner, it has a reciprocal link with the spinal cord, more specifically the cervical one with neck muscles involved in head posture and movements. Electrophysiological studies in cats, rats, and humans reported excitatory cervical reflex responses after electrical stimulation of sensory afferents in the trigeminal ganglion or cutaneous stimulation of facial skin (Altersmark et al., 1992; Ertekin et al., 1996; Sumino and Nozaki, 1977). In addition, Abrahams et al. (1979) demonstrated that chin-tap stimulation inhibited both masticatory and cervical muscle contraction, this result indicating functional motor coupling between trigeminal and cervical systems. The sternocleidomastoid muscle could be inhibited by the same trigeminal stimuli that produced masseter muscle inhibition (Browne et al., 1993). Short latency trigemino-cervical reflexes were similarly obtained in humans following stimulation of the infraorbital branch of the trigeminal nerve (Di Lazzaro et al., 1996). The reflex extension of the head in swimming, provoked by the contact of the nose area with water, is another example of the triggering from trigeminal afferents to head and neck mobility (cited by Manni et al., 1975). Response latency suggested, at a minimum, a di-synaptic pathway mediated by trigemino-spinal neurons mainly located in pars oralis of the spinal trigeminal nucleus or a trisynaptic trigemino-reticulo-spinal pathway mediated by trigeminal neurons from the same oral subnucleus and adding a premotor neuron in the reticular formation (Altersmark et al., 1992; Di Lazzaro et al., 1996). Besides short trigeminal pathways to motor neurons of the cervical spinal cord, neuroanatomical works provide evidence of trigeminal bilateral projections to the dorsal horn of the cervical spinal cord. By combining anterograde and retrograde tracer techniques, central axons of

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proprioceptive afferent neurons originating in masticatory muscles with cell bodies located in the mesencephalic trigeminal nucleus were observed in the medullary parvicellular reticular formation as far as the C3 segment of the spinal cord (Shigenaga et al., 1988a), suggesting a role played by jaw-closing muscle proprioception during jaw and neck movements. This trigeminal projection from primary afferent neurons to the cervical dorsal horn was confirmed by other studies in rats (Jacquin et al., 1983; Pfaller and Arvidsson, 1988), guinea pigs (Segade et al., 1990), and monkeys (Wang and May, 2008). Marfurt and Rajchert (1991) demonstrated the origin of bilateral trigemino-spinal projections from neurons in both mandibular and ophthalmic divisions of the trigeminal ganglion and a termination at higher levels of dorsal spinal cord, preferentially of C1-C3 segments but as far as C7. Considering the trigemino-spinal projecting fibers from the ophthalmic nerve, they conveyed certainly proprioceptive inputs from the extraocular muscles (Buisseret-Delmas and Buisseret, 1990). For the trigemino-spinal projecting fibers originating from the mandibular division, they arose predominantly from the inferior alveolar, mylohyoid and auriculotemporal nerves and were possibly of the Aß type (Segade et al., 1990). Originating, for example, from lip sensors, periodontal receptors or temporo-mandibular joints (Frayne et al., 2016), they conveyed information on mandibular position in space. The upper cervical dorsal horn is known to receive also large primary afferents from the dorsal root ganglia (Kerr, 1972; Pfaller and Arvidsson, 1988) and more particularly neck muscle afferents (Nyberg and Blomqvist, 1984). Marfurt and Rajchert (1991) suggested, therefore, the existence of a convergent spinal and trigeminal projecting zone with possible termination on common second-order neurons. All these results provide evidence that trigeminal projections to the cervical spinal cord may play roles in the coordination and stabilization of head posture and gaze, this hypothesis being supported by the additional existence of projecting fibers to the cuneate and vestibular nuclei as well as the cerebellum (Jacquin et al., 1982; Marfurt and Rajchert, 1991). Second order bilateral projections were also distributed from the spinal trigeminal nucleus to the spinal cord, predominantly in ventrolateral

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regions of oralis and interpolaris subnuclei recognized to be involved in transmitting sensory information from posterior and lateral parts of the head and face (Matsushita et al. 1982; Ruggiero et al., 1981). A mapping of these trigemino-spinal neurons revealed a cell body location in trigeminal nuclear zones similar to those of the trigemino-tectal and trigemino-cerebellar neurons (Ruggiero et al., 1981). Moreover, the findings of spino-trigeminal projections, from the rostral levels of the cervical spinal cord to the trigeminal interpolaris subnucleus (Neuhuber and Zenker, 1989), and their organization in a spatial overlap with the trigemino-spinal fibers permitted to suspect functional reciprocal loops between the two structures and integration of trigeminal and spinal information through feedback mechanisms (Phelan and Falls, 1991). By coupling tracer experiments with immunohistochemical detection of glutamate and glutamic acid decarboxylase (GAD), the synthetic enzyme of GABA, Diagne et al. (2006) proposed a more functional approach in the trigemino-spinal fiber network investigation. By observing labeled neurons in the ventral parts of the trigeminal caudal oralis and rostral interpolaris subnuclei after tracer injection in the upper cervical spinal cord, they confirmed previous results obtained in rats (Matsushita et al., 1982; Ruggiero et al., 1981). In regard to the ventral location of the cell bodies in the nuclei, they supposed that these trigemino-spinal fibers conveyed sensory information from the ophthalmic region (Capra and Dessem, 1992; Nord, 1967), certainly from the extraocular muscles (Ogasawara et al., 1987; Buisseret-Delmas and Buisseret, 1990; Porter and Donaldson, 1991). On the other hand, they distinguished two pools of neurons in approximately equivalent proportions among fibers projecting to the spinal cord, trigeminal neurons presumably containing either glutamate with an excitatory effect or GABA with an inhibitory effect. These results suggest an implication of extraocular proprioception in the modulatory role played by trigemino-spinal pathways in the coordination of eye and head movements (Diagne et al., 2006). Moreover, by anterograde and retrograde tracer injections, respectively, in ventrolateral part of the spinal trigeminal nucleus and spinal cord, they demonstrated the existence of a trigemino-vestibulo-spinal pathway by identifying double

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labeling mainly in the ipsilateral inferior and ventral part of the lateral vestibular nuclei. Referring to previous neuroanatomical studies (Buisseret-Delmas et al., 1990, 1999; Edney and Porter, 1986; Pfaller and Arvidsson, 1988; Pinganaud et al., 1999, Porter and Donaldson, 1991; Sato et al., 1997), the data indicated a functional convergent zone for extraocular and neck proprioceptive information in the inferior and lateral vestibular nuclei (Diagne et al., 2006; Valla et al., 2003) and attested another part of the neuroanatomical substrate for the cervical and vestibular reflexes serving gaze and balance. Although the influence of eye muscle proprioception on neck muscle activity seems logical in regard to the required coordination between eye and head orientated movements, Manni et al. (1975) showed that it is not a specific effect of eye proprioceptive afferents, since it can be elicited by stimulating other trigeminal receptors. In the previous section, we reported mandibular afferent projections to inferior and medial vestibular nuclei, more moderately to the lateral one (Buisseret-Delmas et al., 1999; Diagne et al., 2006). Therefore, we cannot refute a possible implication of oral somatosensory and stomatognathic afferents in this indirect trigeminovestibulo-spinal pathways as well. Eye function is also relevant in oral function such as jaw-catching food, swallowing, or chewing. Studies reflected a trigeminal influence at different levels of the oculomotor system: 1) In the previous section, we reported the existence of first- and second-order trigeminal information to medial and superior vestibular nuclei including the prepositus hypoglossi and interstitial nuclei (Buisseret-Delmas et al., 1990; Marfurt and Rajchert, 1991; Pinganaud et al., 1999), considered as preoculomotor regions responsible for vestibulo-ocular reflexes. 2) The superior colliculus is a crucial visuomotor integration center. Receiving visual, somatosensory, and proprioceptive afferents, it constructs a polysensory map of the environment for orienting behaviors and acts as a premotor structure in head and eye movements (Büttner-Ennever et al., 1996). Huerta et al. (1981;

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1983) were the first to show, in the cat, the existence of fibers originating from the trigeminal spinal interpolaris and oralis subnuclei to deep and intermediate gray layers of the superior colliculus. These results were confirmed in the same species (Harting et al., 1997; Wiberg et al., 1986) but also in rodents (Bruce et al., 1987) and monkeys (Wiberg et al., 1987). The trigemino-tectal fibers conveyed somatosensory information from the face, particularly the periocular (Ndiaye et al., 2002) and perioral (Bruce et al., 1987) regions and the distribution pattern of the perioral fibers on the tectum was equivalent to the vibrissal representation in the periphery (Belford and Killackey, 1979). In return, the superior colliculus sends inputs to the brainstem trigeminal nuclear complex and the orbicularis oculi motoneuronal zone of the facial motor nucleus (Dauvergne et al., 2004), indicating a tectal role in eye and eyelid movements. Reciprocal connections were also demonstrated between neurons located in the caudal part of the mesencephalic trigeminal nucleus and the superior colliculus (Ndiaye et al., 2000). As these trigeminal fibers are in charge of proprioceptive information from extraocular or jaw muscles and periodontal receptors, the authors suggested a role played by the superior colliculus in the control of associated oculomotor and oral functions. 3) The oculomotor nuclei are also targets of trigeminal efferents. Neural projections were traced from the trigeminal sensory nuclear complex to the oculomotor and trochlear nuclei in addition to the trigeminal and facial motor ones (Guerra-Seijas et al., 1993; Pinganaud et al., 1999; Xue et al., 2006). Specifically, afferent fibers activated by corneal and periorbital stimulation showed a terminal field location in the ventral part of the trigeminal principal and spinal oralis nuclei similar to that of neurons projecting to the oculomotor nucleus (May et al., 2012). Activation of this trigemino-oculomotor pathway induced inhibitory post-synaptic potentials in levator motor neurons, reflecting the neuroanatomical substrate of the blink reflex (Ledoux et al., 1997; May et al.,

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Catherine Strazielle and Magali Hernandez 2012). A neural tract was also traced from jaw-closing muscle proprioception directly to the oculomotor and trochlear nuclei in an amphibian, possibly to stare at the prey while catching it with the jaws (Hiscock and Straznicky, 1982). Similar oculomotor projections were obtained in rats (Luo et al., 1991). Consecutive down-stretching of the mandible induced Fos expression in oculomotor neurons (III-IV) and also in neurons of the interstitial nucleus of Cajal, a pre-oculomotor region (Liang et al., 2017). Electrotonic coupling phenomenon existing in the mesencephalic trigeminal nucleus between the cluster-organized afferent neurons from different origins (Curti et al., 2012; Xing and Yang, 2014) may be another mechanism for oculomotor neuron activation (Liang et al., 2017).

All these functional networks controlling head and eye movements may be incomplete without counting on first- and second-order trigeminocerebellar pathways. Similar to the vestibulo-cerebellar ones, they project onto ipsilateral lobules involved in equilibrium and muscle tonicity (Carleton and Carpenter, 1984; Huerta et al., 1983; Marfurt and Rajchert, 1991; Matsushita et al., 1982; Strazielle et al., 1994).

3.4. The Trigeminal System in Body Balance: Clinical Studies in Human The anatomical and functional relationships between the two proprioceptive systems of the cranio-facial complex argue in favor of a significant role of the trigeminal system in the control of head posture, not only during dynamic mandible movement but also during static activity. Vestibular information participates not only in head equilibrium but also in balance of the entire body with complementing information provided by body position sensors. The posture platform is an important tool for exploring body balance in humans. It is constituted with a base on which a bare-foot person is subjected to displacements of the underlying

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supporting surface. The posture platform is used with body position sensors and electromyography for evaluation of standing support with open and closed eyes in static and phasic conditions (Horak et al., 1994). The vestibular system works in combination with proprioception and vision to promote postural stability, but even on a perfectly stable support surface, a standing person will sway slightly. Two parameters are generally analyzed: (1) body sway and (2) sway area covered by the center of foot pressure as an indicator of postural balance (Geurts et al., 1993). Body sway is considered to reflect the energy consumption needed for the person to remain steady. As head position and equilibrium are involved in body balance, afferent information involved in the control of head posture should be pertinent for body balance control as well. Although the visual system is unnecessary for static position of the head (Graybiel, 1974), visual information largely contributes to maintain body balance, since body sway is greater when the eyes are closed. It was hypothesized that head and jaw positions with dental occlusion affect body sway as well (Fujimoto et al., 2001; Yoshida et al., 2008). For the last twenty years, numerous studies have used this tool to test the influence of trigeminal afferents, notably periodontal proprioception, on postural stability and gait control. The data showed that different jaw relations implied also differences in body posture. In comparison to maximal intercuspidation and mandibular rest position, a myocentric position which assures a right-left equilibrated tonic activity in the muscles of the mandible improved postural balance in the frontal plane (Bracco et al., 2004). In a similar study, balance control and stabilization in body movements (shooting performances) were observed when occlusion was artificially set on the centric relation (Gangloff et al., 2000), providing a facial symmetric position owing to equilibrated forces between structural elements of the temporal-mandibular joint and a tonic contraction of the jaw muscles (Woda et al., 2001). These results reflect the relation between mandibular position and head posture sustained by the intermingled pathways present between the trigeminal, vestibular, spinal, and oculomotor systems (Pinganaud et al., 1999; Buisseret-Delmas et al., 1999; Diagne et al., 2006). It has been suggested that a more symmetric maxillar-mandibular position results in a more

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symmetric sternocleidomastoid muscle contraction pattern and less body sway. Therefore, a good balance of masticatory and head and neck muscles seems to be an important factor for postural stability (Browne et al., 1993; Sumino and Nozaki, 1977). An asymmetric production of mandibular proprioceptive cues by means of anesthesia of the inferior alveolar nerve (Gangloff and Perrin, 2002) deteriorated significantly postural control and displaced the center of foot pressure in the contralateral side of anesthesia when the eye was closed, certainly as a consequence of the loss of visual cues able to compensate the sensory alteration. A more recent study (Yoshida et al., 2008) showed that toothless subjects had a larger sway area and body sway when standing with eyes closed than normal subjects. Moreover, in the test group, denture wearing did not improve postural stabilization. It was thus suggested that periodontal proprioceptive afferent stimulation provided by the natural tooth indirectly contributes to head posture through mandibular stability. However, the role of these dental afferents seemed minor in regard to the predominant role played by the visual system, body posture being unaffected when eyes were open, focusing on a cue. On the other hand, Perinetti (2006) found no posturographic correlation between dental occlusion and head posture with no significant difference between the mandibular rest position and dental intercuspidation, either in open or closed eye conditions. Similar results were obtained with three dental occlusion conditions (rest position, maximal intercuspidation, and thwarted asymmetrical occlusion) and eyes open or closed in a static upright stance task (Tardieu et al., 2009) considering the main contribution of otolithic input and vestibular function in static head position (Graybiel, 1974). Nevertheless, postural control was affected by dental occlusion when the platform was unstable and the eyes closed (statistical interaction) in the sense of a significantly higher energy cost for the thwarted laterality occlusion (Tardieu et al., 2009); the latter corresponds to a non-centric occlusion inducing an asymmetrical unbalanced position of the mandible. In parallel, there is in guinea pigs a trigeminal contribution only to the dynamic phase of righting function (Troiani et al., 1981). The results are coherent with the notion that dental

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proprioceptive afferents have a weak influence on postural control under normal physical conditions but gain in importance in altered conditions with impoverished sensory cues. However, studies indicate that postural control may depend more on proprioceptive information from joint and jaw muscles resulting from the mandibular position imposed by the dental occlusion than to a direct effect from periodontal sensation. We have seen previously that hemilabyrinthectomized guinea pigs lose the benefit of compensatory responses after ipsilateral trigeminal neurotomy of the trigeminal nerve (Petrosini and Troiani, 1979). We may therefore conclude that vision and somatosensory signals are reliable indicators of head posture and balance. Considering the trigeminal system, it must not be forgotten that, except for stomatognathic afferents, extraocular muscle afferents constitute an important contributor to postural control (Weir et al., 2000). It was found that, in a dark condition, the body sway was lower with open than closed eyes, possibly because of the muscular tonicity underlying extraocular proprioception affecting balance and postural control (Fox, 1990; Guerraz and Bronstein, 2008).

CONCLUSION The numerous studies reported in this argumentation show that the trigeminal system exerts its influence in all sensory-motor structures invested in static and dynamic postural control of the head, participating in the regulation of muscle tonicity, postural adjustments and eye stabilization. They revealed a complex network of short and multisynaptic reflexes integrating the trigeminal system in vestibulo-oculo-spinal functional loops at different sensory, premotor, and motor levels. A schematic representation of the multiple functional neuroanatomical pathways is proposed in Figure 2. The trigeminal implication is evident by the way it conveys and processes extraocular muscle proprioception valuable for gaze control. However, studies have proved that stomatognathic proprioception is involved in this complex network as well,

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a fact absolutely understandable when considering that we can eat when swinging or talk when running or with one’s head down.

Figure 2. Schematic organization of the brainstem neuroanatomical network processing head posture and movements. The vestibular nuclear complex integrating prepositus hypoglossi and interstitial nuclei in addition to the four vestibular nuclei is the center of the functional mechanisms. It establishes reciprocal connections with the sensory structures (thin arrows), specifically the trigeminal sensory nuclear column of the brainstem, the main and lateral cuneate nuclei (= cuneate n.) and the dorsal horn of the cervical spinal cord, all interconnected between them along with the ponto-medullary reticular formation. The vestibular nuclear complex and reticular formation are the main producers of fibers constituting the medial longitudinal fasciculus (MLF) responsible for the motor order distribution by way of an important network of interconnections (bold arrows) in all the efferent structures involved, namely the oculomotor and orofacial nuclei, and the ventral horn of the cervical spinal cord. The cerebellum and superior colliculus, premotor structures for the control of head and eye movements, are interconnected with all afferent and efferent structures engaged in the mechanisms. In the case of a vestibular deficit, compensation is provided strongly by vision (bold arrow) and more moderately by dental occlusion (dotted arrow). To simplify the diagram, the trigeminal and spinal pathways for the monosynaptic myotatic reflexes as well as cuneate connections on suprasegmentar structures are not reported.

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Tolu, E; Caria, MA; Chessa, G; Melis, F; Simula, ME; Podda, MV; Solinas, A; Deriu, F. Trigeminal motoneuron responses to vestibular stimulation in the guinea pig. Arch Ital Biol, 1996, 134, 141-51. Tolu, E; Pugliatti, M. The vestibular system modulates masseter muscle activity. J Vestib Res, 1993, 3, 163-71. Tolu, E; Pugliatti, M; Lacana, P; Chessa, G; Caria, MA; Simula, ME. Vestibular and somatosensory afferents modulate masseter muscle activity. J Vestib Res, 1994, 4, 303-11. Torisu, T; Yamabe, Y; Hashimoto, N; Yoshimatsu, T; Fujii, H. Head movement properties during voluntary rapid jaw movement in humans. J Oral Rehab, 2001, 28, 1144-52. Torvik, A. Afferent connections to the sensory trigeminal nuclei, the nucleus of the solitary tract and adjacent structures. An experimental study in the cat. J Comp Neurol, 1956, 106, 51-142. Torvik, A; Brodal, A. The origin of reticulo-spinal fibers in the cat. An experimental study. Anat Rec, 1957, 128, 113-37. Troiani, D; Petrosini, L. Neuronal activity in the vestibular nuclei after trigeminal stimulation. Exp Neurol, 1981, 72, 12-24. Troiani, D; Petrosini, L; Passani F. Trigeminal contribution to the head righting reflex. Physiol Behav, 1981, 27, 157-60. Valla, J; Delfini, C; Diagne, M; Pinganaud, G; Buisseret, P; BuisseretDelmas, C. Vestibulotrigeminal and vestibulospinal projections in rats: retrograde tracing coupled to glutamic acid decarboxylase immunoreactivity. Neurosci Lett, 2003, 340, 225-8. Waite, PME; Tracey, DJ. Trigeminal sensory system. In: G. Paxinos (ed.) The rat nervous system. London: Academic Press, 1995:705-17. Walberg, F. On the morphology of the mesencephalic trigeminal cells. New data based on tracer studies. Brain Res, 1984, 322, 119-23. Walberg, F; Dietrichs, E; Nordby, T. On the projections from the vestibular and perihypoglossal nuclei to the spinal trigeminal and lateral nuclei in the cat. Brain Res, 1985, 333, 123-30. Wang, N; May, PJ. Peripheral muscle targets and central projections of the mesencephalic trigeminal nucleus in macaque monkeys. Anat Rec, 2008, 291, 974-87.

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In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 8

THE BRAINSTEM AND HALLUCINATIONS Michael Serby, MD *,1, Nicole Derish, MD 1 and David Roane, MD 2 1

Mount Sinai Beth Israel Medical Center and Icahn School of Medicine at Mount Sinai, New York, NY US 2 Lenox Hill Hospital, New York, NY US

ABSTRACT Many hallucinations may arise from or involve brainstem structures. This chapter will explore the evidence for brainstem involvement in the genesis of hallucinations according to sensory modality, i.e., auditory, visual, olfactory, gustatory and tactile systems. Brainstem areas, including medulla, pons and midbrain, are central way stations in the auditory pathway and these areas contribute to the perceived nature of sound in multiple ways. Lesions anywhere in this system could have an impact on hearing and lead to the development of auditory and musical hallucinations. In schizophrenia, for example, auditory input, perhaps representing peripheral or brainstem deficiencies, might contribute to release of inner verbal stimuli. There is evidence supporting the role of the brainstem in the development of visual hallucinations, particularly in

*

Corresponding Author Email: [email protected].

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Michael Serby, Nicole Derish and David Roane the context of peduncular hallucinosis or of degenerative dementias. The brainstem has a role in modulating visual stimuli and helps determine how they are processed in cortico-thalamic structures. It also has a role in the sleep-wake cycle, which may be related to visual hallucinations. As to other sensory modalities, future research and clinical observation may further support a brainstem basis for or contribution to olfactory and/or gustatory hallucinations. There is, however, already reason to believe that the brainstem may play an active role in generating and/or modulating tactile hallucinations.

1. GENERAL INTRODUCTION The pathophysiology underlying hallucinatory experiences may be complex and varied. Clinical and research attention has focused on neuroanatomical and functional changes in cortical and subcortical areas. Many hallucinations may arise from or involve brainstem structures. This chapter will explore the evidence for brainstem involvement in the genesis of hallucinations according to sensory modality, i.e., auditory, visual and tactile systems. Substantial evidence supports pontine and higher brainstem contributions to the production of auditory, including musical, hallucinations (AH and MH) (Branco e Silva and Dozzi Brucki, 2010; Cascino and Adams, 1986; Celesia, 1970; Serby et al., 2013). Normally, sound is projected from the ear to the cochlear nucleus in the pons, where it is processed before ascending via known pathways to the auditory cortex. Interruptions to the input from the ear (diminished hearing or deafness), as well as damage to the cochlear nucleus and related structures, may lead to faulty signaling to the auditory cortex, resulting in release phenomena, e.g., AH. Visual hallucinations (VH) may also be stimulated by brainstem mechanisms on occasion. An uncommon phenomenon, peduncular hallucinations, represents just such a pathologic occurrence. This chapter will review the relationships of various types of hallucinations to brainstem structure, function and pathology.

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2. AUDITORY HALLUCINATIONS AND THE BRAINSTEM 2.1. Introduction Auditory hallucinations are disturbing manifestations of various neuropsychiatric disorders, including schizophrenia, psychotic mood disorders, delirium and anatomic brain lesions. The AHs are usually described as voices, although other qualities may predominate, most notably in the case of musical hallucinations (MHs). The occurrence of AHs may be accompanied by delusional beliefs about their nature and source. Many people may, however, retain intact insight into these phenomena. The contribution of brainstem structures to the development of AHs cannot be understood without knowledge of the anatomy of the auditory system (Figure 1). Sound transmission originates in the ear, projects to the brainstem, and then ascends to subcortical and cortical areas (afferent and efferent pathways). The cochlear nerve originates from neurons in the spiral ganglion of the cochlea, then enters the medulla, proceeding to the cochlear nucleus. Ascending pathways from the superior olivary complex and along the lateral lemniscus lead to the inferior colliculus, the auditory center of the midbrain. The inferior colliculus is central to various aspects of audition, including sensitivity to frequency, intensity, and volume. From here fibers leave the brainstem and reach the medial geniculate body of the thalamus before projecting to the auditory cortex in the temporal lobe. There are also descending efferent pathways from the cortex, inhibiting or modulating the afferent input from below. These fibers terminate in the pontine cochlear nucleus. It can be seen that brainstem areas, including medulla, pons and midbrain, are central way stations in the auditory pathway and that these areas contribute to the perceived nature of sound in multiple ways (Celesia, 2015; Pickles, 2015). Lesions anywhere in this system could have an impact on hearing and lead to various sequelae, e.g., deafness, tinnitus, AH and MH.

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A2.Musical Hallucinations A number of reports have found significant brainstem lesions underlying the onset and presence of MH (Branco e Silva and Dozzi Brucki, 2010; Cascino and Adams, 1986; Murata et al., 1994; Serby et al., 2013; Schielke et al., 2000). For example, small pontine infarcts may produce MH acutely, particularly in the presence of hypoacusis in the elderly (Serby et al., 2013). The disruption of auditory pathways, including the cochlear nucleus, olivocochlear bundle, superior olivary complex, and acoustic stria, presumably leads to disinhibition, an increase in the “noiseto-signal” ratio, with release of “inner speech” or other perceptual traces. Although non-musical hallucinations may occur in the context of decreased auditory input (brainstem lesions and/or significant hearing loss) (Cascino and Adams, 1986), studies have focused largely on the presence of MHs in these situations. The separate appearance of musical and nonmusical hallucinations suggest that there may be slightly different anatomical pathways within the auditory system to accommodate these sensory phenomena. It is interesting to note a recent study that demonstrated distinct cortical pathways for music and for speech (NormanHaignere et al., 2015).

2.2. Schizophrenia and Verbal Hallucinations Although numerous studies have reported functional/anatomical abnormalities related to the appearance and intensity of auditory verbal hallucinations (AVH) in schizophrenia, the emphasis has exclusively been on cortical and, to some extent, subcortical structures. There is considerable evidence that there are changes in auditory cortex and in other brain areas corresponding to the sensing of AVHs in schizophrenia (Allen et al., 2012; Glaser et al., 2004; Lennox et al., 2000; Simons et al., 2010). For example, structural imaging has shown that the presence and severity of AVH are associated with gray matter reductions in temporal regions, including primary auditory cortex (Glaser et al., 2004). Functional imaging studies have also supported the concept of cortical dysfunction leading to

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AVHs in schizophrenia (Lennox et al., 2000; Simons et al., 2010). Oscillations in activation of the parahippocampal gyrus have been demonstrated and may represent “an aberrant trigger of activations in language-related areas responsible for AH” (Allen et al., 2012). Whatever the cortical changes are, studies suggest that the mechanism is specific to AHs in general and are not limited to schizophrenia. Patients who are hearing voices may have an underlying inability to “self-monitor inner speech.” Thus, there appears to be a failure to suppress activation of left superior temporal cortex during “inner speech.” (McGuire et al., 1995). None of these studies has provided any data on either structural or functional abnormalities in the critical brainstem areas subserving audition. There is no way of knowing whether this is a significant oversight or is warranted. The fact is, though, that cortical inhibitions, stimulations and oscillations could in part be modulated by afferent and efferent projections to and from the brainstem. Considering schizophrenic AVHs in the light of potential peripheral and brainstem pathology, it might be important to explore any possible contribution of such changes. Studies that shed light on this question are lacking. There is a report from 1995 that compared narrative speech perception in normal controls, non-hallucinating patients with schizophrenia, and hallucinating patients with schizophrenia. Those who hallucinated differed significantly from the other two groups in that they clearly demonstrated impaired speech perception (McGuire et al., 1995). This finding suggests that auditory input, perhaps representing peripheral or brainstem deficiencies, might contribute to the release of inner stimuli.

2.3. Conclusion on Auditory Hallucinations In summary, there is some evidence of brainstem contributions to the perception of AHs. The literature on MHs provides significant support for this relationship. It remains to be seen whether there are analogous changes underlying the presence of AVHs. Reduced sensory input and/or changes in modulation by afferent and efferent brainstem pathways may play a role.

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Acoustic area of temporal lobe cortex

Medial geniculate body

Brachium of inferior colliculus Inferior colliculus Midbrain Correspondence between cochlea and acoustic area of cortex: Low tones Middle tones High tones

Lateral lemnisci Nuclei of lateral lemnisci

Medulla oblongata

Superior olivary complex Dorsal cochlear nucleus Inferior cerebellar peduncle Ventral cochlear nucleus Cochlear division of vestibulocochlear nerve

Intermediate acoustic stria

Dorsal acoustic stria Reticular formation Trapezoid body (ventral acoustic stria)

Inner Spiral ganglion

Outer Hair cells

Figure 1. (© Elsevier, with permission).

3. VISUAL HALLUCINATIONS AND THE BRAINSTEM 3.1. Introduction Visual hallucinations (VH) appear in a variety of clinical contexts associated with brain diseases, psychiatric disorders such as schizophrenia, and neuropsychiatric disorders of old age, including Lewy body dementia and Parkinson’s disease. Visual hallucinations are strongly correlated with central nervous system (CNS) lesions and sensory pathology in contrast to AHs (Burns et al., 1990). This does not imply AHs lack a biological substrate, but rather refers to the close association between well-defined anatomical lesions of the central nervous system and the appearance of VH.

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The human brainstem is involved in regulating normal sleep architecture and is significantly implicated in the regulation of autonomic stability, as well as modulation of a series of sensory systems, especially auditory and visual modalities. Along with a large variety of fiber tracts, the human brainstem harbors the origins of the ascending dopaminergic, cholinergic, noradrenergic and serotonergic projection systems and is the target of the descending serotonergic system, which is integrated into the so-called “gain getting system” of the brainstem. Intercalated between these anatomically and functionally well-defined gray brainstem components are the highly integrative and coordinating components of the neural network of the reticular formation. The role of the brainstem in generating VH has not been fully elucidated and a better understanding of the contribution of this anatomical region could contribute to improved clinical assessment and treatment. A better understanding of the pathology of VH and the role of lesion location can be obtained by reviewing the anatomy of the visual system (Figure 2).

Figure 2. (© Sage, with permission).

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Optical information originates from the retina, is transmitted to the thalamus, where it receives input from the brainstem before reaching the visual cortex. The optic nerve originates from retinal neurons, information passes along the optic nerve and optic tract into the lateral geniculate nucleus (LGN) of the thalamus, where it receives input from the superior colliculus via the pulvinar nucleus and then traverses the optical radiation through the temporal lobe into the visual cortex. The LGN can be considered the center of this tract, as it receives information directly from the retina via the optic tract as well as from brain stem structures. The brainstem inputs information, via the ascending pathway to the pulvinar nucleus, which has a central role in establishing the salience of visual stimuli (associated with eye movement). Basal projections from excitatory cholinergic centers (parabigeminal and parabrachial nuclei) (Mocellin et al., 2006) and inhibitory serotoninergic centers (dorsal raphe nuclei) (Manford and Andermann, 1998) modulate the excitatory tone of the LGN (Figure 3).

Figure 3. (© Sage, with permission).

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Lesions at any level of this system may result in the generation of visual hallucinations. This includes well-described irritation of cortical centers responsible for visual processing (such as seizure activity, migraines with aura), lesions in the proximal visual system, and lesions in afferent structures that modulate these cortical areas (such as brainstem pathologies), which may result in hyperexcitability and generate VH at a cortical level.

3.2. Peduncular Hallucinosis Jean Lhermitte (1922) described in a published report, the case of a 72year-old woman with acute onset of visual hallucinations and disturbance in her sleep-wake cycle. Lhermitte hypothesized that the hallucinations represented the equivalent of a “dreamy state” and noted that these lesions were not localizable to any CNS region known to be associated with visual processing and analysis. Lhermitte pointed out that the neurological examination of the patient showed a complete left oculomotor palsy, left abducens paresis, right arm paresthesia, dysmetria and Babinski sign, which altogether suggested infarction involving the midbrain and pons. The patient would describe the hallucinations as animals with strange appearance, people in costumes or children playing. She was aware that the hallucinations were not real but nevertheless tried to touch them at times. Van Bogaert (1924) reported another case, only two years later of a 59year old female with rheumatic heart disease who also developed hallucinations involving animals, in the context of acute onset of vertigo, diplopia and ataxia. Eventual autopsy of this patient revealed extensive paramedian midbrain infarction involving the cerebral peduncle and the cerebellar peduncle as well as the medial substantia nigra and the red nucleus. For this reason, van Bogaert (1927) proposed the term “l’hallucinose pédonculaire” (peduncular hallucinosis) to describe this phenomenon. Subsequently, this term was applied to any VH associated with lesions of the midbrain and diencephalon. Further autopsy-proven cases of peduncular hallucinations were described with a similar pattern of clinical findings.

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With the availability of Magnetic Resonance Imaging (MRI), it became possible to demonstrate that so-called “peduncular hallucinations” are, in fact, not restricted to the peduncular area. VH were also associated with lesions of the midbrain gray matter and the tegmentum (Geller and Bellur, 1987), the posterior paramedian and centromedian thalamus or the pulvinar (Feinberg and Rapcsak, 1989). Miller Fisher (1991) suggested replacing the term peduncular hallucination with “brainstem hallucination”; however, the previous nomenclature persisted and is still the most common term used to describe visual hallucinations associated with brainstem dysfunction. The pathomechanism of neurogenic hallucinations is understood as a possible consequence of an irritation of ascending brainstem pathways. This is frankly different from cortical visual hallucinations; such as those found in focal epilepsy, that are most often interpreted as a release phenomenon. PH, that is typically associated with hypersomnolence and oculomotor disturbance, may occur with cognitive impairment (McKee et al., 1990), although the published reports are inconsistent regarding the characteristic presentation and would benefit from larger samples to characterize patients’ behavior. Generally speaking, peduncular hallucinations will begin a few days post-infarction and often subside several weeks after onset. In some cases, they persist for years (Manford and Andermann, 1998). Hallucinatory episodes generally have lasted for a duration of minutes to hours and occur more frequently in the evening. It is infrequent to find visual hallucinations in combination with other types of sensory hallucinations, although in some cases (Branco e Silva and Dozzi Brucki, 2010) co-occurring auditory hallucinations have been described.

3.3. Visual Hallucinations in Lewy Body Dementias Lewy body dementias (LBD) may include both Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB). While the clinical presentation of these two diseases can differ, they each reflect the

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same neuropathologic process leading to the aggregation of alphasynuclein inclusions, better known as Lewy Bodies or Neurites. Over time there is a prominence of non-motor symptoms, such as cognitive impairment, abnormal sleep patterns, behavioral disturbances and visual hallucinations. Visual hallucinations are a common non-motor symptom of Lewy body dementias. Among the possible mechanisms underlying these VH is a hypothetical role for brainstem pathology. This chapter focuses on aspects of the brainstem potentially relevant to the underlying explanation of VH in LBD. When the first cases of VH in Parkinson’s disease began receiving attention, this symptom was linked to the use of levodopa (Celesia and Barr, 1970). Further studies shed sufficient light to discourage the “dopaminomimetic therapy theory” as the sole etiology of VH. It is now understood that VH are a frequent non-motor manifestation of LBD (Onofrj et al., 2013) and an intrinsic component of the illness. Goetz et al. (2010) demonstrated this in the prospective study involving nonhallucinating patients with Parkinson’s disease. Over the course of 10 years over 60% of these patients developed VH, suggesting this symptom may be part of the natural history of this disease. An interactive model of visual hallucinations suggests that for this symptom to occur, both visuoperceptive and attentional system disruption may need to be present (Collerton et al., 2005). Lewy bodies are primarily seen in the cortical and subcortical brain regions but are also present in other areas of the CNS, such as the brainstem. Lewy bodies affecting the cholinergic, dopaminergic, noradrenergic and serotoninergic neurons in the ascending tracts from the midbrain and pons could manifest in the altered thalamocortical processing of visual stimuli, as proposed by Schmeichel et al. (2008) in patients with Lewy bodies and Parkinson’s disease. This may be supported by the results of a therapeutic trial with rivastigmine, a cholinesterase inhibitor, which reduced the presence of VH in patients with PDD. Similarly, it is well known that anticholinergic drugs cause VH with increasing frequency in this patient population. (Diederich et al., 2009). Goetz et al. (2010) found a

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consistent association between the presences of visual hallucinations and sleep pathology in LBD. REM Behavior Disorders (RBDs), co-occurring with VH and cognitive fluctuations may suggest impairment of cholinergic mechanisms modulating REM sleep and thalamocortical processing (Schmeichel et al., 2008). Sleepiness could be understood as a disease-drug interaction, due to lesions in neural systems (noradrenergic, serotonergic and orexinergic) exposing patients to increased risk of REM sleep disturbances and possibly VH. As mentioned, there are also inhibitory serotoninergic afferents from the dorsal raphe nuclei (Manford and Andermann, 1998). A disturbance in this area might result in excitation of the dorsal lateral geniculate nucleus (LGN) of the thalamus and the lateral pulvinar and the generation of VH at the cortical level. These structures also have an important role in processing the salience of visual stimuli (Grieve et al., 2000) and regulating retinal inputs. The dorsal raphe nuclei also have a putative role in the sleep-wake cycle (Abrams et al., 2004) that is frequently impaired in LBD, suggesting serotoninergic involvement in the pathophysiology of this disease. Visual hallucinations are often accentuated in states of reduced consciousness and sleep-associated VH are seen commonly in LBD (Mocellin et al., 2006). Ultimately, the presence of Lewy bodies in structures related to autonomic stability, such as the spinal cord intermediolateral cell column, hypothalamus, and dorsal vagal nuclei (Barber et al., 2001), and in the periaqueductal gray area of the midbrain, may correlate with excessive daytime sleepiness observed in these patients (Benarroch et al., 2009) and further facilitate the precipitation of VH.

3.4. Conclusions on Visual Hallucinations In summary, there is evidence supporting the role of the brainstem in the development of visual hallucinations, particularly in the context of peduncular hallucinosis or degenerative dementias. The brainstem has a modulatory role of visual stimuli and how they are processed in the

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corticothalamic structures. It also has a role in the sleep-wake cycle, also presumably related to VH.

4. OLFACTORY, GUSTATORY, TACTILE HALLUCINATIONS AND THE BRAINSTEM 4.1. Olfactory Hallucinations and the Brainstem The olfactory nerve is one of only two cranial nerves that do not originate in the brainstem. Literature relating olfactory hallucinations (OH) to brainstem function and dysfunction has been generally non-existent until quite recently. It has now been shown that phasic raphe nuclei activation results in rapid changes in odorant coding via sensitization of olfactory system mitral cells and modulation of mitral cell responses, affecting pattern separation of smells (Kapoor et al., 2016). An optogenetic study has demonstrated that dorsal raphe serotonergic neurons may inhibit the spontaneous electrical activity of primary olfactory cortex neurons (Lottem et al., 2016). Given this evidence of brainstem modulation of olfaction at various anatomical points, it is interesting to note the paucity of clinical information supporting this link. Perhaps an example of missed opportunities to clarify such a linkage can be found in a report of hallucinations related to a brainstem infarct in a 22-year-old man (Lo et al., 2011). The case report notes migraine-related AHs as a prominent symptom. There is a statement that “strong odors triggered an attack.” The authors do not speculate that these odors may have actually been brainstem-induced OHs. It is certainly true that OHs associated with psychomotor seizures may be described as strong and noxious and may be experienced as an aura. It is, therefore, possible that future research and clinical observation may further support a brainstem basis for or contribution to OHs.

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4.2. Gustatory Hallucinations and the Brainstem In contrast to the sense of smell, there is a clear-cut brainstem anatomical source for regulation of taste, i.e., fibers originating in the nucleus tractus solitarii (NTS) in the medulla. A recent study in rats demonstrated odor-specific responses in areas of the NTS and parabrachial nucleus of the pons (Sammons et al., 2016). There is also evidence of serotonergic control of raphe nucleus origin of specific taste aversion in mice (Iwai et al., 2015). However, to date, no clinical studies or case reports have linked the brainstem to the appearance of gustatory hallucinations.

4.3. Tactile Hallucinations and the Brainstem The somatosensory system traverses through the brainstem as it conveys afferent and efferent signals between peripheral tissues and brain. It is certainly conceivable that brainstem regions may be involved physiologically in the perception of tactile hallucinations (TH). Disorders that manifest TH include delirium tremens, drug reactions (notably cocaine), Parkinson’s disease, delusional parasitosis, and phantom limb syndrome. Although the focus of clinical attention has been on cortical areas and the thalamus (Braun et al., 2003), there is some evidence that brainstem mechanisms may subserve the development of TH. Two case reports document TH following brainstem injury (Branco e Silva and Dozzi Brucki, 2010; Hashimoto et al., 1995). There is, then, reason to believe that the brainstem may play an active role in generating and/or modulating these pathological perceptions.

5. HALLUCINATIONS AND THE BRAINSTEM: CONCLUSION Relatively little attention has been paid to the role of the brainstem in the generation and modulation of hallucinations of various modalities.

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There is, however, evidence of pathophysiologic involvement of these regions in virtually all types of abnormal percepts. Disorders ranging from phantom limb to schizophrenia to strokes may all present hallucinatory disturbances that are influenced by medullary, midbrain and pontine regions. It is clear that our understanding of these relationships is limited, leaving room for greater clarity. More case reports and studies may shed additional light on this matter.

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Kapoor, V; Provost, AC; Agarwal, P; Murthy, VN. Activation of raphe nuclei triggers rapid and distinct effects on parallel olfactory bulb output channels. Nature Neurosci, 2016, 19, 271-82. Lennox, BR; Park, SBG; Medley, I; Morris, PG; Jones, PB. The functional anatomy of auditory hallucinations in schizophrenia. Psychiatry Res, 2000, 100, 13-20. Lhermitte, J. Syndrome de la calotte du pedoncule cérébral. Les troubles psycho-sensoriels dans les lesions du mésocéphale. Rev Neurol, 1922, 38, 359-65. Lo, YL; Hameed, S; Rumpel, H; Chan, LL. Auditory hallucinations and migraine of possible brainstem origin. J Headache Pain, 2011, 12, 573-5. Lottem, E; Lorincz, ML; Mainen, ZF. Optogenetic activation of dorsal raphe serotonin neurons rapidly inhibits spontaneous but not odorevoked activity in olfactory cortex. J Neurosci, 2016, 36, 7-18. Manford, M; Andermann, F. Complex visual hallucinations. Clinical and neurobiological insights. Brain, 1998, 121, 1819-40. McKee, AC; Levine, DN; Kowall, NW; Richardson, EP. Peduncular hallucinosis associated with isolated infarction of the substantia nigra pars reticulata. Ann Neurol, 1990, 27, 500-4. McGuire, PK; David, AS; Murray, RM; Frackowiak, RSJ; Firth, CD; Wright, I; Silbersweig, DA. Abnormal monitoring of inner speech: a physiological basis for auditory hallucinations. Lancet, 1995, 346, 596600. Mocellin, R; Walterfang, M; Velakoulis, D. Neuropsychiatry of complex visual hallucinations. Austral New Zeal J Psychiatry, 2006, 40, 742-51. Murata, S; Naritomi, H; Sawada, T. Musical auditory hallucinations caused by a brainstem lesion. Neurology, 1994, 44, 156-8. Norman-Haignere, S; Kanwisher, NG; McDermott, JH. Distinct cortical pathways for music and speech revealed by hypothesis-free voxel decomposition. Neuron, 2015, 88, 1281-96. Onofrj, M; Taylor, JP; Monaco, D; Franciotti, R; Anzellotti, F; Bonanni, L; Thomas, A. Visual Hallucinations in PD and Lewy body dementias: old and new hypotheses. Behav Neurol, 2013, 27, 479-93.

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Pickles, JO. Auditory pathways: anatomy and physiology. In: GG Celesia, G Hickok (eds) Handbook of clinical neurology, vol 129 (3rd series): The human auditory system. Amsterdam: Elsevier, 2015:3-25. Sammons, JD; Weiss, MS; Escanilla, OD; Fooden, AF; Victor, JD; DiLorenzo, PM. Spontaneous changes in taste sensitivity of single units recorded over consecutive days in the brainstem of the awake rat. PlosOne, 2016, 11(8), e0160143. Schielke, E; Reuter, U; Hoffmann, O; Weber, JR. Musical hallucinations with dorsal pontine lesions. Neurology, 2000, 55, 454-5. Schmeichel, AM; Buchhalter, LC; Low, PA; Parisi, JE; Boeve, BW; Sandroni, P; Benarroch, EE. Mesopontine cholinergic neuron involvement in Lewy body dementia and multiple system atrophy. Neurology, 2008, 70, 368-73. Serby, MJ; Hagiwara, M; O’Connor, L; Lalwani, AK. Musical hallucinations associated with pontine lacunar infarcts. J. Neuropsychiatry Clin Neurosci, 2013, 25, 153-6. Simons, JP; Tracy, DK; Sanghera, KK; O’Daly, O; Gilleen, J; Dominguez, M-d-G; Krabbendam, L; Shergill, SS. Functional magnetic resonance imaging of inner speech in schizophrenia. Biol Psychiatry, 2010, 67, 232-7. Van Bogaert, L. Syndrome inférieur du noyau rouge, troubles psychosensoriels d’origine mesoencephalique. [Lower red nucleus syndrome, psycho-sensory disorders of mesoencephalic origin.] Rev Neurol, 1924; 40: 423. Van Bogaert, L. L’hallucinose pédonculaire. [Hallucinosis peduncular.] Rev Neurol, 1927, 47, 417-23.

In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 9

THE BRAINSTEM AND AGGRESSION Rodrigo Narvaes and Rosa Maria Martins de Almeida Institute of Psychology, Laboratory of Experimental Psychology, Neuroscience and Behavior, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

ABSTRACT The serotonergic system comprehends a wide range of activities in the Central Nervous System, the Peripheral Nervous System and in the neurons of gastro-enteral pathway. In this chapter, we discuss the biosynthesis, the function and the degradation of serotonin in the brain, as well as how it interacts and regulates other systems and behaviors, the therapeutic uses of its receptors and its transporter. Finally, we debate over the role serotonin plays in aggressive behavior, at functional and dysfunctional levels.



Corresponding Author: Institute of Psychology, Federal University of Rio Grande do Sul, 2600 Ramiro Barcelos St, Porto Alegre, 90035-003 Rio Grande do Sul, Brazil. E-mail addresses: [email protected], [email protected] (R.M.M. de Almeida).

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1. SEROTONIN 5-hydroxy-tryptamine (5-HT), commonly known as serotonin, participates in many diverse functions in the central nervous system and acts as a global homeostatic regulator of emotion, mood, appetite, and sleep, as well as a regulator of sexual and motor activity (García-Alcocer et al., 2010). The involvement of serotonergic neurotransmission in a number of neurological and psychiatric conditions has been widely documented in recent years (Hornung, 2003). Serotonin is a monoaminergic neurotransmitter, and it has the widest set of projections among its family; in fact, the axons of the serotonergic neurons located in the raphé nuclei reach every single structure in the brain – but its main effect is in the prefrontal cortex and the mesolimbic system. Serotonin levels are known to be involved in the regulation of social behavior, including aggressions, and its action is mediated by an enormous array of different receptor families and subtypes (Guiard and Di Giovanni, 2015). All serotonin produced in the brain derives from a set of structures known as the raphé nuclei, formed mostly by serotonergic neurons. The serotonergic neuron clusters may be allocated, on the basis of their distribution and main projections, into two groups: the rostral group, confined to the mesencephalon and rostral pons, with major projections to the forebrain, and the caudal group, extending from the caudal pons to the caudal portion of the medulla oblongata, with major projections to the caudal brainstem and to the spinal cord. This antero-posterior division in two populations has been recently corroborated by genetic studies revealing their origins in separate precursor populations (Hornung, 2003). The biosynthesis of serotonin is a process composed by two steps. First, the enzyme tryptophan hydroxylase (TPH) converts tryptophan (TRP) into 5-hydroxytryptophan (5-HTP). Then, 5-HTP is decarboxylated by the enzyme aromatic-amino acid-decarboxylase (AADC) into 5-HT (Mosienko et al., 2014). TPH is the rate-limiting enzyme in the process. In 2003, two independent serotonergic systems were discovered in vertebrates – peripheral and central – controlled, respectively, by TPH1 and TPH2 (Walther et al., 2003). At steady state, the synthesis of serotonin, its

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intraneuronal metabolism and its spillover to the plasma must be equivalent – the sum of these three rates is called “serotonin turnover,” used to evaluate the function of the serotonergic metabolism (Figure 1; Barton et al., 2008).

Figure 1. Serotonin synthesis, degradation and turnover. Tryptophan hydroxylase converts TRP into 5-HTP, which is then converted into 5-HT by the aromatic amino acid decarboxylase; b) serotonin may flow to the circulation after leaving the cell or (c) stay in the synapse; d) the 5-HT transporter may then carry serotonin back into the presynaptic serotonergic neuron or leak into the axoplasm (e); f) sequestration by the presynaptic neuron may happen and then lead to (g) degradation by MAOA into 5-HIAA. Modified from Barton et al, 2008.

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The final metabolite of serotonin degradation is the 5-hydroxy-indoleic acid (5-HIAA), and its degradation is performed by an enzyme named monoamine oxidase with two isoforms- A and B (MAO-A and MAO-B). MAO is a mitochondrial bound flavoenzyme that catalyzes oxidative deamination of xenobiotics and biogenic amines. MAO-A preferentially metabolizes bulky endogenous amines such as serotonin, noradrenaline and adrenaline; MAO-B metabolizes small exogenous amines such as benzylamine and penethylamine (Basu et al., 2016). Due to the intense role played by MAO-A in the regulation of serotonin levels, inhibitors of MAO-A activity can be used as antidepressants, but their use is restricted to a last resort, since they can interact with other drugs; more critically, it is imperative that MAO-A is never combined with selective serotonin reuptake inhibitors – the combination of these two types of antidepressants creates a cycle in which serotonin from the synaptic cleft takes longer to be taken back into the neuron and, when it finally is reenters the cell, its degradation is halted. This hyperactivation of serotonergic mechanisms is known as “serotonin syndrome” and can lead to death (Nisijima, 2015).

1.1. Raphé Nuclei and Serotonin Production As characterized by Dahlströhm and Fuxe (1964), the raphé nuclei include a diverse collection distributed along the midline of the brainstem and the primary source of serotonergic projections to the forebrain, brainstem, and spinal cord. Initially, the authors identified the raphé nuclei as 9 serotonin-producing regions (from B1 to B9); nowadays, it can also be considered that there are six raphé nuclei (three in each group), plus a neuronal population in the caudal group, with each nucleus having a distinct function. The rostral group contains the caudal linear nucleus (CLi), the dorsal raphé nucleus (DRN) and the medial raphé nucleus (MRN) and it corresponds to 85% of the serotonin production in the brain. The dorsal raphé nucleus is a bilateral, heterogenous brainstem nucleus, located mainly in the ventral part of the periaqueductal gray matter of the midbrain

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(Michelsen, 2007) (Figure 2), and most of the innervations of the forebrain originate from this region (Andrade, Huereca, Lyons, Andrade and McGregor, 2015). The DRN can be divided into five subregions: interfascicular, ventral (or ventromedial), ventrolateral (or lateral), dorsal and caudal. Besides, it may also be divided along the rostrocaudal axis into a rostral, middle and caudal portion. All subregions, except for the caudal, are located from the rostral to the middle portions of the DRN (Michelsen, 2008). The MRN is divided into a medial region (MRN proper), complemented dorsally by the nucleus pontis oralis (NPO) and ventrally by the supralemniscal nucleus (SLN). Over 80% of the neurons in the medial region synthesize serotonin, a proportion that falls dramatically in the lateral divisions of the nucleus; however, the SLN contains more serotonergic neurons than any other non-DRN region. The serotonergic neurons in the caudal linear nucleus have a characteristic morphology and some of them may express the catecholamine synthesizing enzyme tyrosine-hydroxylase, while others contain substance P. Serotonergic neurons in the CLi are ten times less numerous than in the dorsal or medial raphé nuclei. The caudal group amounts to a maximum of 15% of the total population of serotonergic neurons, and contains the raphé magnus nucleus (NRM), the raphé obscurus nucleus, the nucleus raphé pallidus (NRP), and the lateral reticular formation. The NRM is the biggest of the regions in the caudal group (approximately 30,000 neurons) and is known to be involved with facilitative systems of pain (Hattori et al., 2010). About one-quarter of its neurons are serotonergic and they play important and multifactorial physiological roles, due to their strategic location and presence of ascending, descending and horizontal afferent and efferent connections (Inuyushkin et al., 2010). The nucleus raphé pallidus constitute the smallest group in the raphé system (about 1,000 neurons). The nucleus raphé obscurus is located above the nucleus pallidus and is involved in the regulation of sexual behaviors. Finally, the lateral reticular formation is the second biggest cluster of serotonergic neurons in the medulla, with approximately 18,000 cells.

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Figure 2. Schematic representation of the position of the Dorsal (DRN) and Medial raphé nuclei (MRN) in the rat brain (coronal sections; bregma -7.8 mm). Abbreviations: Aq, cerebral aqueduct; Cg Central gray; XCSP, decussation superior cerebellar peduncle. Modified from Ayala et al, 2015.

The complex network of afferent and efferent connections from the raphé nuclei demonstrates the relevance of the serotonergic system to the brain. The interactive mechanisms between serotonin and other neurotransmitters involve a multitude of receptors and its transporter.

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1.2. 5-HT Transporter In both somatodendritic and synaptic compartments, the availability of serotonin is actively constrained by the high-affinity, antidepressantsensitive 5-HT transporter (5-HTT or SERT); alterations in its expression and function have been implicated in a range of neurobehavioral disorders, including anxiety, depression, obsessive-compulsive disorder and autism (Ye et al., 2016). SERT is a peptide that mediates re-uptake of released serotonin into the presynaptic terminal and thereby terminates synaptic signal; this process also ensures a replenishment of the intracellular 5-HT stores (Larsen et al., 2015). This is the mechanism of action for a class of antidepressants known as SSRIs (Selective Serotonin Reuptake Inhibitors); by inhibiting the reuptake of 5-HT from the synaptic cleft, those substances induce a persistence of the serotonergic signaling without increasing the production levels of serotonin or using agonists, which would have a pleiotropic and less specific effect. SERT is also targeted by serotoninnorepinephrine reuptake inhibitors. This is the case for widely used drugs such as citalopram, escitalopram, paroxetine and fluoxetine. SERT is also involved in the neurotoxic mechanism induced by 3,4 methylenedioxy-methamphetamine (MDMA), popularly known as “ecstasy.” MDMA can bind to SERT and enter 5-HT nerve terminal via the transporter that facilitates the release of 5-HT from the storage vesicles. This acute increase in 5-HT levels in the nerve terminal triggers a rapid accumulation of hydrogen peroxide, a by-product of metabolism by monoamine oxidase B (MAO-B), which is converted into hydroxyl radical to induce oxidative stress in mitochondria of serotonergic neurons (Shih et al., 2015). SERT can also be targeted by hormones, such as testosterone, as will be discussed later in this chapter.

1.3. 5-HT Receptors There are seven currently known families of 5-HT receptors: 5-HT1, 5HT2, 5-HT3, 5-HT4, 5HT5, 5-HT6 and 5-HT7. They are present in several

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regions of the brain and are a part of the regulation of many functions, from mood to memory (Bert et al., 2008). With the exception of 5-HT3, all receptor families are G-coupled proteins; 5-HT3 is the only family with ligand-gated ion channels (also known as ionotropic receptors; Lanfumey and Hafon, 2004). 1.3.1. 5-HT1 Receptors The 5-HT1 type comprehends five different receptors (5-HT1A, 5-HT1B, 5-HT1D, 5-HT1E and 5-HT1F; originally, there were six receptors in this family, but 5-HT1C was later considered too similar to receptors of the 5-HT2 family and was therefore moved to it). 5-HT1 is the largest of the seven families (Lanfumey and Hafon, 2004). 5-HT1A is one of the most extensively characterized of all 5-HT receptors and it is known to be involved with memory, cognition, social behaviors, physiological responses, neural development and plasticity. All 5-HT1 receptors are present both in the CNS and peripherally. In the hippocampus, it is involved with memory consolidation; in the prefrontal cortex, it regulates both inhibition of aggression and reaction to unfairness. It is also known to be involved in anxiety and depression; buspirone, a derivate of azapirone, is the first of the 5-HT1A receptor agonists to be used in the treatment of anxiety. 5-HT1A and 5-HT1B exist as inhibitory autoreceptors on serotonergic neurons (5-HT1A on the soma and dendrites in the raphé nuclei; 5-HT1B on the axon terminals), whereas they are largely inhibitory postsynaptic heteroreceptors in the serotonin system’s terminal fields. 5-HT1A receptors are also known to be down-regulated by the use of SSRIs – the reason for this, however, is still unknown. It is interesting to note that receptors in the 5-HT1 family are highly expressed in several types of cancer. 5-HT1D receptors are less known to be involved in neurotransmission and more related to other physiological effects, such as renal outflow (García-Pedraza et al., 2015) and nausea (both 5-HT1A and 5-HT1D are targets for antiemetic drugs, which reduce and interfere in vomiting). Neither the function nor the distribution of 5-HT1E receptors are well known in mammals, but some studies indicate that it is involved in the

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regulation of hippocampal serotonergic activity due to its inhibition of the adenylate cyclase activity in the dentate gyrus, which would make 5-HT1E receptors a valid target for the treatment of neuropsychiatric diseases associated with memory deficit, such as Alzheimer’s (Klein and Teitler, 2012). 5-HT1B, 5-HT1D and 5-HT1F receptors are valid therapeutic targets for the treatment of migraines with a group of anti-migraine drugs called triptans. 5-HT1B mRNA is densely localized within smooth muscle, and less in the endothelium of cerebral blood vessels; this distribution has been shown to mediate the vasoconstrictive properties of this class of drugs (Mitsikostas and Tfelt-Hansen, 2012). 5-HT1D receptors are effective in animal models but not clinical trials – the precise mechanism of this divergence is still to be unraveled. Alternatively, 5-HT1F receptors are known to relieve acute migraine without vasoconstriction (Ramadan et al., 2003). While both 5-HT1B and 5-HT1D receptors are well known to be located in the blood vessel and regulate constriction and dilatation, the activity of 5-HT1F receptors are believed to happen in the physiology of the blood-brain barrier instead, as suggested by Cohen et al., (1999). All three receptors are widely expressed in astrocytes. 1.3.2. 5-HT2 Receptors The 5-HT2 family is formed by three receptors: 5-HT2A, 5-HT2B and the receptor formerly known as 5-HT1C, which was found out to be much more similar to those in the 5-HT2 group, and was therefore moved to this family and renamed to 5-HT2C. The receptors in this family, just like the 5HT1 family, are involved in aggression and in a wide array of physiological responses; however, they are mostly known for playing a role in neuropsychiatric diseases and in memory regulation. 5-HT2 receptors can induce mitochondrial biogenesis and repair some types of mitochondrial dysfunction, as demonstrated by Rasbach et al. (2010). 5-HT2A is one of the principal post-synaptic receptors and is localized in the cortex, ventral striatum, hippocampus and amygdala, and it is expressed in both excitatory and inhibitory cells (Morici et al., 2015). All those brain structures are involved in processes associated with memory:

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formation, consolidation, reconsolidation and extinction; as a matter of fact, 5-HT2A has emerged as a possible therapeutic target for treating Alzheimer’s disease. The signaling mechanism of this receptor is a complex one, and involves activation of the Gq pathway and a key Betaarrestin 2 – knockout mice for Beta-arrestin 2 do not show any behavioral response to 5-HT2A agonists. 5-HT2A has a high rate of co-expression with 5-HT1A in pyramidal cells of the cortex, which might indicate a cooperative function for the encoding of excitatory inputs into action potential firing; the precise mechanism of this cooperation, however, remains unclear. Due to the intense involvement of 5-HT1A receptors of the cortex in the regulation of aggression, which will be discussed later in this chapter, one might consider that this co-expression can also help to elucidate the role of 5-HT2A receptors in aggressive behavior. Besides, 5-HT2A has been identified in various brain regions that regulate emotionality, such as amygdala, hippocampus, thalamus and several cortical areas (entorhinal, cingulate, piriform and frontal cortices) which are also, though the mechanism of this action by 5-HT2A is not clear yet, related to epilepsy. Since emotionality plays a key role in both mood and cognition, it is not a surprise that this receptor is also involved in depression. In fact, 5-HT2A receptors have been detected in all monoaminergic brainstem levels, such as the raphé nuclei and the ventral tegmental area. While SSRIs were generally thought to affect only SERT, it is now known that the five (fluoxetine, norfluoxetine, citalopram, escitalopram and paroxetine) most common drugs of this group are also very potent agonists of 5-HT2B receptors in astrocytes and neurons, but not of any other 5-HT receptors (Peng et al., 2014). More interestingly, they are shown to be equipotent – unlike their action in SERT, which has different rates of specificity. In fact, it is possible to use non-SSRI drugs that target 5-HT2B to induce SSRI-like behavioral effects. However, this effect was strongly reduced when 5-HT2B receptors were deleted, which led to the conclusion that 5-HT2B receptors in the raphé nuclei are required for SSRIs to have their therapeutic action. In addition, the chronic stimulation of 5-HT2B receptors in astrocytes can induce changes in the metabolism of glutamate, glucose and glycogen – and since glutamate is a precursor to GABA, and

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GABA has a regulative effect in serotonergic metabolism due to its action in the raphé nuclei (see: Interactions between serotonin, hormones and other neurotransmitters, later in this chapter), these metabolic alterations can alter a wide range of brain functions (Hertz et al., 2015). Astrocytic 5-HT2B receptors levels also appear to be involved in the depressive phenotype in a mouse model of Parkinson’s disease. The involvement of 5-HT2B receptors in the amnesia induced by the injection of harmaline into the CA1 area of the hippocampus implies involvement of this receptor in the processing of memory - a role shared by the other receptors in this family as well (Nasehi et al., 2014). 5-HT2C receptors are known to be involved in the serotonergic activity in all brain areas. Non-selective agonists and inverse agonists to this receptor – molecules that can bind to a receptor, but induce an opposite response to what would be expected from a ligand to that receptor – can cause reduction in motor activity or promote increases, or abnormalities, in motor activities (Navailles et al., 2013). These drugs can also alter the expression of C-Fos, an immediate-early gene (and a proto-oncogene as well) involved in a huge array of brain activities, ranging from aggression to metabolism. 5-HT2C receptors are also well known targets for antidepressants, and several drugs (such as amitriptyline, mianserin and trazodone) act as antagonists to this receptor, some of them due to interaction between 5-HT2C receptors and the dopaminergic system. 1.3.3. 5-HT3 Receptors The 5-HT3 family is the only non-protein G coupled of all the receptor families; rather, they are pentameric ionotropic receptors belonging to the family of cys-loop ligand-gated ion channels. They are formed by an array of five types of subunits - 5-HT(3A) to 5-HT(3E). 5-HT3C, 5-HT3D and 5-HT3E, however, are currently known only in humans – other mammals show only the subtypes A and B. The binding of serotonin to a 5-HT3 receptor leads to a fast excitatory response from the neuron (Niesler et al., 2007). Each receptor is composed by either five 5-HT3A subunits (homopentameric and called 5-HT3A receptors) or one or more 5-HT3A

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subunit and one of the other four subunits (heteropentameric). Hence, 5-HT3A is the only subunit that can form functional homopentameric channels. Only the subunits 5-HT3A and 5-HT3B have been extensively studied. They are expressed in the CNS in the regions responsible for vomiting, pain, reward system, cognition and anxiety control (Kudryashev et al., 2016). Receptors expressing 5-HT3A are associated with the modulation of gamma waves, believed to be essential for binding neuronal assemblies in the brain for various cognitive processes, such as memory and sensory responses - both processes that can be significantly influenced by emotional states (Huang et al., 2016). In fact, while the activity of 5-HT3A receptors is not required to acquire or maintain fear memories, its action is essential to the process of extinction of that memory, as demonstrated by Kondo et al., (2014). The currently available antagonists for 5-HT3 receptors are ondansetron, granisetron, dolanestron, palonsetron, ramosetron, alosetron and tropisetron. The first five are used to treat chemotherapy-induced and post-operative nausea and vomiting – all of those molecules have structural similarity to 5-HT. Alosetron is available for irritable bowel syndrome. The antiemetic action of 5-HT3 receptors might be related to their postsynaptic position in the dorsal vagal complex of the vomiting center (Machu, 2011). Tropisetron is a candidate drug for the treatment of Alzheimer’s disease due to its ability to increase the levels of sAPPα, the precursor to the amyloid-β plaques labeled as responsible for the initial onset of the disease (Spilman et al., 2014). 1.3.4. 5-HT4 Receptors The 5-HT4 receptor is monotonically and inversely correlated with brain serotonin levels – low levels of serotonin result in high binding to this receptor – and is expressed vastly in the hypothalamus, hippocampus, nucleus accumbens, ventral pallidum, amygdala, basal ganglia, olfactory bulbs, frontal cortex, septal area, substantia nigra and fundus striatus (Quiedeville et al., 2015). It is involved in gastro-intestinal function, cognition, memory regulation and aggressive behavior. 5-HT4 agonists are

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widely used as drugs for the treatment of constipation and other gastrointestinal mobility disorders, and it has a promotive effect in the neurogenesis of injured enteric neurons (Takaki et al., 2015). Recently, it was shown in animal models that a chronic treatment with 5-HT4 receptors agonists can decrease the cognitive deficits in learning and memory that are induced by conditions such as anxiety and depression (Darcet et al., 2016). It is now believed that this action is related to the promotion of adult neurogenesis in the dentate gyrus, induced by the binding of serotonin to the 5-HT4 receptors located in that region; these studies used agonists and antagonists, as well as SSRIs and 5-HT4R KO to corroborate this evidence (Imoto et al., 2015). However, hippocampal 5-HT4 receptor expression is inversely correlated with human memory (Meneses, 2015). 1.3.5. 5-HT5 Receptors There are two currently known receptors in the 5-HT5 family: 5-HT5A and 5-HT-5B. However, humans only express the 5-HT5A gene, since the 5-HT5B coding sequence is interrupted by stop codons (Grailhe et al., 2001). 5-HT5 receptors are involved in nociception, memory and metabolic functions, such as the regulation of triglyceride levels in human plasma, as shown by Zhang et al., (2010). 5-HT5A receptors are mainly localized in the cerebral cortex, hippocampus, cerebellum, amygdala, caudate nucleus, hypothalamus, substantia nigra and spinal cord – this receptor has been shown to mediate the antinociceptive effects of 5-HT in the spinal cord of mice (Muñoz-Islas et al., 2014) and is exclusively expressed in the CNS. 5-HT5A receptors are also highly expressed in motoneurons of Onuf’s nucleus, responsible for controlling pelvic functions such as erection, ejaculation and urination; 5-HT2A receptors are expressed in this nucleus as well, but the two receptors are expressed in different populations of motoneurons (Xu et al., 2007). It also has a small inhibitory effect in adenylate cyclase. 5-HT5B receptors have been lost in mammal evolution in the divergence of rodents and humans – this might be related either to a loss of the corresponding function of this receptor or a possible evolutionary

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advantage from its loss – but the precise reason remains to be unraveled. The expression pattern of 5-HT5B in rodents is highly specific: it was thought to be expressed, in both mice and rats, solely in the CA1 pyramidal neurons, in the habenula, which suggests a specific function (most likely involved with memory regulation) (Graihe et al., 2001); however, its mRNA was also found to be expressed in the DRN, which suggests an involvement in aggression as well (Serrats et al., 2004). 1.3.6. 5-HT6 Receptors The 5-HT6 receptor is only located in the CNS, and the highest densities of this receptor are found in the striatum, olfactory bulbs, nucleus accumbens, frontal and entorhinal cortices, and dorsal hippocampus (Quiedeville et al., 2015). Due to its presence in the hippocampus, it is seen as a potential treatment for Alzheimer’s disease, and many agonists and antagonists targeting this receptor are now in clinical trials. Since receptors of this type are only found in the CNS, they limit the possible side-effects, unlike the more systemic distribution of other receptors that may activate other receptors of the same type outside the CNS (Karila et al., 2015). 5-HT6 receptor antagonist idalopiridine, with high affinity for 5-HT6 with low affinity for non-target receptors, is also a potential symptomatic treatment for Alzheimer’s disease when combined with donepezil (an acetylcholinesterase inhibitor, also used to treat Alzheimer’s), since it is known to improve cognition function as well as to be involved in memory and learning. This action happens most likely through the modulation of cholinergic, monoaminergic and glutamatergic systems. Its action as cognitive-enhancer also makes it a valid target for treatment of schizophrenia, which includes potent cognitive deficits in its negative symptoms. Moreover, evidence suggests that SB-742457, an antagonist of 5-HT6 receptors, is involved in the promotion of satiety – which would make 5-HT6 antagonists an interesting treatment for obesity. It is indeed known that some pathways involving appetite and feeding are related to serotonergic and dopaminergic systems (Higgs et al., 2016).

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1.3.7. 5-HT7 Receptors The 5-HT7 receptor is an emerging target for pharmacological intervention – drugs such aripiprazole, amilsulpride, lurasidone and vortioxetine perform their antipsychotic, the former two, and antidepressant effects, the latter, through 5-HT7 receptors. Both the pharmacological blockade and the genetic inactivation of this receptor show an antidepressant effect, unlike other 5-HT receptors, usually activated (either through SSRIs or agonists) to reach this outcome (Stroth and Svenningsson, 2015). This receptor is expressed particularly in the hippocampus, hypothalamus (in the suprachiasmatic nucleus), thalamus and cerebral cortex. While highly conserved (with over 90% of similarity) between mammalian species, it has a low homology with other 5-HT receptors. The 5-HT7 receptor is also involved in memory regulation and the retrieval of fear memory as well as stress-induced defecation. By microinjecting a 5-HT7 agonist into the ventral hippocampus, Ohmura et al. (2015) observed an increase in the response to memory-dependent but not to memory-independent fear. This effect was completely blocked by administering a 5-HT7 antagonist (SB239970) but not by other receptor antagonists. However, injecting the antagonist outside of the ventral hippocampus had no effect. The injection of the effective antagonist in the ventral hippocampus also suppressed freezing behavior and stress-induced defecation. Their work also corroborates the idea that 5-HT7 receptors are expressed much more abundantly in the CA3 region of the hippocampus than in any other region, a region much closer to the amygdala, involved in emotional-processing and fear responses. Lurasidone, a potent antipsychotic drug used in the treatment of the negative and mood symptoms of schizophrenia, acts through both 5-HT7 (as an antagonist) and 5-HT1A (as a partial agonist) receptors, and has strong binding affinity for 5-HT2A and dopamine 2 (D2) receptors as well. The versatility, complexity and ubiquity of 5-HT receptors in the CNS demonstrate the relevance of this monoaminergic system. With a high involvement in a wide array of different functions, it is no surprise that

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serotonin is also highly involved with many other neurotransmitters and hormones, which interfere in 5-HT metabolism in a myriad of ways.

2. INTERACTION BETWEEN SEROTONIN, HORMONES AND OTHER NEUROTRANSMITTERS 2.1. Testosterone Testosterone is the final product of the hypothalamus-pituitary-gonads (HPG) axis. It is an androgen, which alters the CNS formation during neural development resulting in the “male brain” – it is known that chemical castration during brain development can lead to a more femalelike brain structure. The HPG axis consists of three levels: the hypothalamus releases gonadotropin-releasing hormone (GnRH) and luteinizing hormone (LH), together with follicle stimulating hormone (FSH) is released, respectively. LH and FSH are transported to the gonads, where they are responsible for the production of testosterone. The HPG axis shares the first two structures with the HPA axis, responsible for the production of cortisol (in primates) and corticosterone (in other mammals) – these systems have a mutually inhibitory function, in which the HPA axis inhibits the HPG at all levels, while HPG inhibits HPA at the pituitary level (Montoya et al., 2012). This mechanism is important to the regulation of aggression induced by testosterone and cortisol. It was believed that these two hormones regulated aggressive behavior in a dominant way, which raised the dual-hormone hypothesis: the ratio between testosterone and cortisol (T/C ratio) would not only regulate levels of aggression but also the way aggression is expressed (reactive-impulsive, the “hot” and short-lasting type of aggression; or instrumental aggression, which uses social tools and is usually “colder” and goal-oriented) (Mehta and Josephs, 2010). However, it was later shown that serotonin also has a part in this regulation – and, as a matter of fact, it was crucial to both levels and expression of aggression, and both hormones interact with serotonin in

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the regulation of this behavior. While high testosterone and high cortisol levels would lead to higher overall aggression, lower testosterone levels associated with high cortisol levels would not – therefore, it is wise to assume that, while cortisol has also a regulatory function in aggression, testosterone plays a bigger role in the expression of this behavior. Free testosterone concentrations in the cerebrospinal fluid (CSF) are related to an increase in the levels of impulsive aggressive behavior, while 5-HIAA levels are negatively correlated to both overall aggression and inclination to severe aggression. However, while high testosterone is related to a more dominant and competitive behavior, its levels alone are not capable of inducing aggression – aggression requires lower levels of brain serotonin, especially in the cerebral cortex (Birger et al., 2003). One of the possible mechanisms of interaction between testosterone and serotonin is by the reduction in the activity of the medial region of the orbitofrontal cortex (OFC) within the prefrontal cortex (PFC). Androgens are known to downregulate the expression of 5-HT receptor mRNA and decrease serotonin turnover in the PFC – through this pathway, testosterone can both induce aggression and decrease serotonin levels in regions relevant to the regulation of aggressive behavior (Narvaes and de Almeida, 2014). It is worth mentioning, however, that the serotonergic system includes several other brain regions that also affect the prefrontal cortex.

2.2. Cortisol Cortisol (humans) and corticosterone (rodents) are the final products of the HPA axis – the paraventricular nucleus in the hypothalamus produces corticotropin-releasing hormone (CRH) as a response to stress. CRH then promotes the release of adrenocorticotropic hormone (ACTH) by the pituitary, which acts by stimulating the adrenal cortex into producing glucocorticoids (corticosterone and cortisol) (Montoya et al., 2012). The exposure of animals to various stress, such as restraint stress and electroshock, is known to increase serotonin turnover in the nucleus

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accumbens (which integrates the reward system), the amygdala (emotional processing) and the prefrontal cortex –this could lead not only to depressive-like symptoms but also to enhanced aggressive behavior. Prolonged exposure to stress raises chronic cortisol levels, but acute cortisol responses or specific serotonergic challenges are blunted as a consequence of a disturbed cortisol-5-HT1A feedback (Riedel et al., 2002). In humans, the 5-HTP precursors, 5-HTP and L-TRP, stimulate ACTH and cortisol release; however, this does not mean that those mechanisms are necessary for the physiological secretion of cortisol, either basally or during stress (Porter et al., 2004). It is interesting that manipulations of exogenous cortisol lead to an increase in the aggressive behavior of female but not male rats (Böhnke et al., 2010). Both the DRN and the MRN show high levels of expression for glucocorticoid receptors – and since these receptors display low affinity for cortisol (or corticosterone), only high peaks of concentration would be capable of activation (as in stress or the circadian peak of the light-dark cycle) (Chaouloff, 2000). Indeed, stress and glucocorticoids exert major effects on the expression 5-HT1A and 5-HT2A receptors; for example, evidence shows a tonic inhibition of 5-HT1A receptors by adrenal steroids in the hippocampus and in other brain regions that show mineralocorticoid receptors (Leonard, 2005).

2.3. γ-Aminobutiric Acid (GABA) GABA is the main inhibitory neurotransmitter in the mammalian brain. It is a very anciently derived molecule that is also found in plants, fungi, bacteria, cnidarians and insects – and exerts its inhibitory action even in the simplest known of the nervous systems, the hydrozoans (Narvaes and de Almeida, 2014). It is synthesized from glutamate, which also has a function in neurotransmission, and these systems seem to act antagonistically - glutamate is considered the major excitatory neurotransmitter in the brain (Zhou and Danbolt, 2014).

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There are three known GABA receptors (GABAA, GABAB and GABAC). The receptors GABAA and GABAC are ionotropic; GABAB is metabotropic and coupled to a G-protein. The regulation of serotonergic function by GABAergic mechanisms is mostly due to the action of GABAA and GABAB receptors located in the DRN. Positive allosteric modulators of GABAA receptors – molecules that enhance its activity – such as alcohol, benzodiazepines and barbiturates inhibit serotonin release from the raphé nuclei to the prefrontal cortex, which lead to an increase in aggressive behavior; however, direct manipulation of GABA levels leads to a decrease in aggression (Miczek et al., 2003). GABAB manipulations in the DRN can enhance aggressive behavior as well, but that effect ceases when the manipulation happens in the MRN (Takahashi et al., 2010).

2.4. Dopamine Dopamine (DA; 3-hydroxy-tyramine) is a monoaminergic neurotransmitter synthesized from the aminoacid, tyrosine. It is involved in memory regulation, motor coordination and in the reward system, which acts in the mesocorticolymbic system. Although it is known that serotonergic mechanisms control dopaminergic function, it is still unclear how this interaction works (Esposito, 2006). Both neuromodulators behave similarly in a variety of ways, since they can both act by volume transmission at metabotropic receptors to modulate synaptic transmissions in the brain (Jennings, 2013). Serotonin and dopamine are also co-involved in many mental disorders, such as depression and schizophrenia, and the co-administration of both serotonergic and dopaminergic pharmacological tools may prove a valid way of approaching these disorders – even though a recent study using pramipexole (dopamine agonist) and escitalopram (a state-of-the-art SSRI) did not show any increase in effectiveness with the use of both drugs when compared to the use of either of them alone (Franco-Chaves et al., 2013).

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3. AGGRESSION 3.1. Generalities Aggression is a complex social behavior that evolved within the context of protecting and obtaining resources, such as food, territory, reproductive partners and hierarchical status (Nelson and Trainor, 2007). It is commonly defined as an overt behavior that has the intent of causing harm to another individual. The expression of aggressive behavior is a complex phenomenon that involves a multitude of neural networks and brain regions, such as amygdala, prefrontal cortex and raphé nuclei (Figure 3A and 3B). Besides, it also has an important social function in many species of rodents and primates. However, aggressive behavior is extremely expensive in terms of energy and risky to individuals and to their groups: according to the World Health Organization (WHO), the number of fatal victims in interpersonal conflicts was twice as high as the number of war victims in 2002. Despite having a social importance, overt aggression directed to one or more individuals has the potential of altering the neurological functions of all parts involved through phenomena such as the “winner effect” (Kloke et al., 2011) and “social defeat” (Miczek, 1979). As a matter of fact, in the United States, most cases of post-traumatic stress disorder (PTSD) originate not in exposures to warfare and combat, but in much more common events such as criminal victimization and other forms of violence (Stein, 2002).

3.2. Serotonin Serotonin plays a pivotal role in regulating aggressive behavior, mostly through 5-HT1A and 5-HT1B receptors. 5-HT1A agonists such as F15599

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Figure 3A. Aggression mechanisms in rodents: information from the olfactory bulb is processed by the medial amygdala (MEA) and sent to the lateral septum (LAS), bed nucleus of the stria terminalis (BNST) and anterior hypothalamic area (AHA). These areas then prompt the periaqueductal gray (PAG) into inducing species-specific aggressive behavior. Stress, however, can inhibit aggression via its inputs to the orbital frontal cortex (OFC), the hippocampus and the paraventricular nucleus (PVN). Modified from Nelson and Trainor, 2007.

Figure 3B. Aggression mechanisms in nonhuman primates: visual or vocal information activates the medial amygdala (MEA) and is sent to the lateral septum (LAS), bed nucleus of the stria terminalis (BNST) and anterior hypothalamic area (AHA). These areas then prompt the periaqueductal gray (PAG) into inducing aggressive behavior. The orbital frontal cortex (OFC) is thought to mediate the interpretation of social cues and may inhibit the aggressive impulse. Modified from Nelson and Trainor, 2007.

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have already been shown to have anti-aggressive effects when microinjected into the ventral orbital (VO) region of the prefrontal cortex (Stein et al., 2013). Da Veiga et al., (2011) have also shown the influence of another 5-HT1A agonist, 8-OH-DPAT, on the aggressive behavior in postpartum females – it is known that there are many differences in the aggressive behavior in males and females, not only in rat and mice, but also in primates and humans (de Almeida et al., 2015). The serotonergic system is involved in the regulation of aggression in both sexes, but manipulations in the same region can yield different results in males and females (Figure 4). The modulation of aggressive behavior by 5-HT1A and 5-HT1B receptors has one particular difference: while 5-HT1A activation decreases aggression in association with 5-HT levels, the activation 5-HT1B will inhibit aggression despite them. This difference makes 5-HT1B receptors an excellent target for drugs that control aggression – besides, the activation of 5-HT1B receptors might be connected to a modulatory function performed by them in other neurotransmitter systems (Nelson and Trainor, 2007). In humans and other primates, low serotonin levels are usually associated with higher levels of aggressive behavior, usually in association with other molecules. As stated earlier, high testosterone levels associated with low 5-HT levels can induce severe aggression: as a matter of fact, this is one of the main mechanisms believed to be associated with the extremely high levels of aggression found in psychopaths. Moreover, psychopaths usually rely on instrumental aggression, rather than impulsive aggression, which could be associated with the severe impairment in emotional neurocircuitry observed in this disorder. Not only is serotonin associated with the regulation of aggression towards other individuals, it is also involved with the reaction to aggression and defensive aggressive behavior. In silver foxes, artificial selection towards lesser levels of defensive aggression caused a marked reduction of basal serotonin levels in the prefrontal cortex, as shown by Popova (2004). In humans, a study using the Ultimatum Game - a task involving two participants in which one of them receives an amount of

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Figure 4. Mechanisms related to aggression in human males (blue arrows) and females (purple arrows). Arrowheads indicate stimulation; bars indicate inhibition of said area or function. Notice how serotonergic mechanisms are involved regardless of sex. Modified from de Almeida et al, 2015.

money and must make an offer to the other participant; if he accepts the offer, they both receive the amount agreed and if he does not, no one gets anything – showed that men with low serotonin levels had a tendency to refuse offers they considered unfair (Crockett et al., 2008). This task has a very interesting purpose, because when the offer is made, it would be wise to assume that a) the player who makes the offer will make the smaller offer possible to keep most of the money, and b) the player receiving the offer will accept any amount because, currently, he has nothing – that approach is called “Rational Maximization.” As a matter of fact, that was exactly what Jensen et al., (2007) found when they performed an adapted version of the protocol in chimpanzees. Humans, however, have the tendency to punish players for lower offers, and, most likely, that is what motivates the player making the offer to give up a higher amount. It is believed that the act of refusing a low offer is, by itself, a response to aggression and domination – high

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testosterone men have been shown to refuse offers they consider unfair, and then immediately make equivalent offers when offered the chance, and there are strong links connecting high testosterone to dominance in humans and primates (de Almeida et al., 2015). Even though serotonin has been a target of intense research for the last six decades, its mechanisms are still not completely understood. The link between serotonin and aggression is being extensively studied, as well as its connection to other systems, but there are many gaps in the knowledge of how epigenetic mechanisms regulate serotonin production, release and degradation, and which other endocrine and neuronal molecules interact with epigenetic regulators. Due to the involvement of serotonergic mechanisms on a variety of neuropsychiatric and other physiological disorders, further studies in this area are required to enlighten the precise role of serotonin in its wide set of regulatory functions.

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In: The Brainstem and Behavior Editor: Robert Lalonde

ISBN: 978-1-53612-845-1 © 2017 Nova Science Publishers, Inc.

Chapter 10

THE BRAINSTEM, AROUSAL, AND MEMORY Stanley O. King II and Cedric L. Williams University of Virginia, Department of Psychology, Division of Neuroscience and Behavior, Charlottesville, VA, US

ABSTRACT Presentation of novel stimuli or exposure to an unfamiliar environment while learning improves memory for newly acquired experiences. Despite evidence implicating the amygdala in novelty detection, a greater proportion of research on novelty’s influence on cognition has focused primarily on the hippocampus. A putative involvement of the amygdala is derived from studies reporting that placement in a new environment activates amygdala neurons and lesions abolish these cellular responses. Similarly, amygdala neurons elicit maximal levels of firing to novel stimuli relative to firing frequencies produced by presentation of familiar items. The basolateral and central nuclei of the amygdala are most likely to mediate amygdala responses to novelty that may underlie memory improvements. These nuclei are activated by novelty, crucial for directing attention to novel stimuli, and essential to developing memories for emotional events. However, due to the lack of research in this area, little is known about the mechanisms underlying amygdala activation to novel stimuli. One likely mechanism is the capacity for novelty-induced arousal to activate noradrenergic

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Stanley O. King II and Cedric L. Williams systems in the basolateral and/or central nuclei of the amygdala. Indeed, placing rodents in unfamiliar surroundings activate the sympathetic nervous system and produces heightened states of autonomic arousal to enhance the development and formation of new memories. Novelty induced increases in peripheral autonomic output are conveyed to the brain by ascending fibers of the vagus nerve that synapse upon A2 norepineprhine containing neurons in the brainstem, nucleus of the solitary tract (NTS). Chemical inhibition of these brainstem nuclei prevents the beneficial actions of novelty on memory formation. Studies examining the formation of emotionally laden memories indicate autonomic arousal enhances memory by potentiating norepinephrine release in both the basolateral and central nuclei of the amygdala. However, the influence of novelty on activating the noradrenergic system has not been extensively explored in the amygdala. Therefore, the current study examined if novelty affects norepinephrine release in the amygdala and if interactions between novelty and norepinephrine output may be more precisely localized to effects on β-noradrenergic receptors in the basolateral or central amygdala nuclei. In Experiment 1, male Sprague Dawley rats implanted with in vivo microdialysis cannluae were either pre-exposed to the conditioning chamber or given no prior exposure to the chamber (novelty group) 24 hr before conducting microdialysis. The subjects freely explored the apparatus for 5 minutes and comparisons in norepinephrine output in the basolateral amygdala was made between those familiar with the chamber relative to the group that experienced the chamber for the first time. Norepinephrine concentrations sampled from the novelty group were significantly greater than those collected from subjects that were preexposed to the conditioning chamber 24 hours earlier (p < .05). A similar design was developed for the behavioral experiments (studies 2 and 3) wherein animals were either familiarized to the fear conditioning chamber by preexposure or were conditioned in a novel behavioral box with five-auditory tone plus footshock (0.35mA) pairings. Pre-exposed and the non-preexposed novelty group were then given intra-basolateral or central infusions of saline or propranolol (0.3g). Memory for associative learning was assessed two days after conditioning by measuring the percentage of time subjects displayed freezing responses during each of three presentations of the tone conditioned stimulus. Results indicate that the memory enhancing properties of novelty exposure are attenuated by posttraining blockade of β-noradrenergic receptors in either the basolateral and central nuclei of the amygdala. Overall findings suggest that novelty-induced arousal enhances cued fear conditioned memory and this effect is mediated in part through activation of β-noradrenergic receptors in the basolateral and central amygdala nuclei.

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Keywords: novelty, arousal, norepinephrine, -noradrenergic receptors, amygdala, memory, fear conditioning

1. INTRODUCTION 1.1. Molecular Consequences of Novelty on the Brain and Behavior There is a growing body of literature indicating that novelty influences the associative strength of new learning and the depth that these new experiences are encoded into memory. In real world educational settings, students exposed to a novel activity an hour before learning a story or engagement in a visual memory task showed significant improvements in story comprehension and visual memory recall (Ballarini, et al., 2013). Other studies with humans demonstrate that novelty exposure in a spatial virtual environment prior to a word learning task also produced enhancements in the number of to be remembered words relative to controls that were not exposed to novelty (Schomaker, van Bronkhorst and Martijn, 2014). On a deeper level, more empirical based studies indicate that exposure to novelty affects memory by inducing intracellular changes in neurons of limbic structures. For example, brief exposure to a novel environment increases hippocampal levels of signaling complex A-kinase anchoring protein 150 (AKAP150) (Nijholt et al., 2007). This protein is critical in the induction of long-term potentiation (LTP) and consolidating new learning by coordinating the actions of cAMP-dependent protein kinase (PKA) (Lu et al., 2007; Moita et al., 2002). During learning PKA is activated and in turn, phosphorylates its downstream target, cAMPresponse element binding protein (CREB) (Alberini, 2009). Interestingly, CREB is also upregulated after placing rats in a novel environment (Kinney and Routtenberg, 1993; Viola et al., 2000; Winograd and Viola, 2004). Furthermore, novelty enhances the phosphorylation of CREB and this enhancement persists beyond an hour following the novel experience,

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but remains unchanged in subjects exposed to a familiar context (Kinney and Routtenberg 1993). More recent findings demonstrate that the enhancement in new learning produced by novelty, is reduced if noradrenergic or glucocorticoid signaling in the hippocampus is suppressed prior to exposing animals to a novel environment (Liu et al., 2015). Taken together, these findings suggest novelty influences neuronal signaling in brain structures critical for new memory formation. However, few studies examine the effects of novelty on limbic structures beyond the hippocampus, such as the amygdala. The conclusions drawn from these studies are further limited in that the observed cellular changes occur subsequent to receptor activation, but little is known about novelty’s impact on neurotransmitter systems that could induce these cellular changes.

1.2. Does Norepinephrine Mediate the Effects of Novelty on Arousal and Cognitive Processing? The neurotransmitter norepinephrine has long been implicated in the formation and storage of long-term memory and its cellular analog LTP (McGaugh, 2004; Sara, 2009; Tully et al., 2007; van Stegeren 2008). Several reports suggest that norepinephrine modulates memory by activating intracellular mechanisms, such as PKA and CREB, which lead to protein genesis (Hu et al., 2007; Sara 2009). A key role of norepinephrine in mediating neuronal changes in response to novelty exposure is provided by findings showing that extracellular concentrations of this transmitter are significantly elevated in the prefrontal cortex or the hypothalamus following exposure to either a novel illuminated environment or a context containing an unfamiliar rat (McQuade et al., 1999). This finding suggests brain areas that receive norepinephrine input are activated by novelty. A role for norepinephrine is also implied by findings showing that neurons in the locus coeruleus (LC), which provide the major source of norepinephrine to forebrain and limbic structures, display phasic bursts of activity upon initial exposure to an environment

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(Vankov et al., 1995). In contrast, increased discharge in LC neurons is not observed when rats are returned to a familiar context, but the neuronal changes are reinstated when a novel object is placed in the familiar context (Vankov et al., 1995). Similarly, behavioral and EEG correlates of sustained attention that are elevated from exposure to a novel environment are abolished in rats given selective lesions of the LC (Gompf, 2010).

1.3. A Contribution of the Amygdala in Influencing the Arousing Actions of Novelty on Memory Other findings report similar changes in amygdala activity in response to novelty. For example, amygdala neurons in primates display maximal rates of firing to novel stimuli but firing frequencies are reduced as test items become increasingly familiar (Wilson and Rolls, 1993) or are abolished by amygdala lesions (Prather et al., 2001). Brief exposure to a novel open field in low or high light conditions also affect neuronal activity in the amygdala as these conditions cause a significant increase in the number of basolateral neurons that express c-Fos relative to home cage or handled control groups (Hale et al., 2006, 2008). Studies examining the neural mechanisms that underlie orienting behavior find the central nucleus to be critical for directing attention to novel stimuli (Holland and Gallagher, 1999). In addition to these nuclei being impacted by novelty, both the basolateral and central nucleus are essential for memory formation in emotionally arousing learning paradigms, as lesions or inhibition of neuronal activity within either of these nuclei significantly impairs memory (Maren, 2004; McGaugh 2004; Wilensky et al., 2006). The separate behavioral, electrophysiological and neurochemical findings suggest that amygdala functioning may represent a significant component of the underlying processes permitting novelty to improve memory. However, this view and the contribution of norepinephrine in mediating these novelty-induced changes in the amygdala have not been investigated. Given this shortcoming, the present studies examined if the mnemonic consequences of novelty exposure are mediated through

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norepinephrine activation of the central and/or basolateral nuclei of the amygdala. As such, the primary objective of Experiment 1 was to assess with in vivo microdialysis, whether arousal related processes associated with novelty exposure to an unfamiliar context impacts norepinephrine release in the basolateral amygdala. The rationale for this study is based upon the finding showing that novelty induced increases in peripheral autonomic output are conveyed to the brain by ascending fibers of the vagus nerve that synapse upon brainstem noradrenergic neurons in the NTS (King and Williams, 2009). These neurons provide dense noradrenergic projections to the LC (VanBockstaele, Peoples and Telegran, 1995) and central amygdala nucleus (Ricardo and Koh, 1978). Moreover, chemical inhibition of NTS brainstem nuclei prevents the beneficial actions of novelty on memory formation (King and Williams, 2009). Since previous studies demonstrate that NTS neurons play a crucial role in memory by initiating norepinephrine release in both the amygdala (Hassert, Miyashita and Williams, 2004; Miyashita and Williams 2002) and hippocampus (Miyashita and Williams 2004) via the LC, Experiment 1 will determine if the arousal related consequences of novelty exposure are mediated in part through elevations in norepinephrine release in the amygdala. Experiments 2 and 3 were designed to reveal if novelty-induced facilitation of Pavlovian fear conditioning requires noradrenergic activation of the central or basolateral amygdala. If exposure to unfamiliar environments increases neuronal activity in LC cells that innervate the amygdala (Cedarbaum and Aghajanian 1978; Nitecka et al., 1980; Vankov et al., 1995), then novelty should produce robust changes in extracellular concentrations of norepinephrine in the amygdala of newly exposed animals relative to subjects that have been habituated to the training context. Moreover, if noradrenergic synapses within the central and basolateral amygdala contribute to the novelty-dependent memory enhancement for fear conditioning, then blocking β-noradrenergic receptors in either of these structures should attenuate the improvement in fear memory produced by novelty exposure.

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2. MATERIALS AND METHODS 2.1. Subjects Seventy-seven male Sprague-Dawley rats (275-300g) obtained from Charles River Laboratories (Wilmington, MA) were used in experiments 1 (n = 10), 2 (n = 33) and 3 (n = 34). Rats were individually housed in plastic cages and maintained on a standard 12:12 hour light-dark cycle with lights on at 7:00 am. Food and water were available ad libitum during the 7-day undisturbed adaptation period to the vivarium. All experiments were conducted in accordance to the policies and guidelines of the University of Virginia’s Animal Care and Use Committee.

2.2. Surgery Each rat received an injection of atropine sulfate (0.1 mg/kg, i.p., American Pharmaceutical Partners, Inc., Schaumburg, IL) followed 10 minutes later by an injection of the anesthetic sodium pentobarbital (50 mg/kg, i.p., Abbot Laboratories, North Chicago, IL). A midline scalp incision was made and microdialysis cannulae or microinjection guide cannulae (15mm, 25.0 gauge, Small Parts, Miami Lakes, FL) were implanted bilaterally 2 mm above the basolateral amygdala (AP: −3.0; ML: ±5.0 from bregma; DV: −6.7 from the skull surface) for rats in experiments 1 and 2. For animals in experiment 3, microinjection cannulae were implanted bilaterally 2 mm above the central amygdala (AP: −2.8; ML: ±4.3 from bregma; DV: −6.5 from the skull surface). Stereotaxic coordinates for all experiments were adapted from the atlas of Paxinos and Watson (1986). Guide cannulae and skull screws were anchored to the skull with dental cement and the scalp was closed with sutures. Stylets (15 mm, 00 insect dissection pins) or microdialysis dummy probes were inserted into the injection cannulae to maintain cannula patency. Penicillin (0.1 ml, i.m., Fort Dodge Animal Health, Fort Dodge, IA) was administered immediately after surgery along with the analgesic buprenex

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(0.05 ml s.c., Hospira, Inc., Lake Forrest, IL) to alleviate post surgical discomfort. The rats remained in a temperature-controlled chamber for at least 1 h following surgery and were given 7 days to recover before the start of each study.

2.3. Behavioral Apparatus and Procedures The apparatus used for microdialysis novelty exposure experiments and Pavlovian fear conditioning consisted of a Coulbourn behavioral chamber (12” W x 10” D x 12”H, Model #: H13-16) that was enclosed in a larger sound-attenuating box (28”W x 16”D x 16”H). The front and back walls of the chamber were made of clear plastic with stainless steel sides and a removable stainless steel grid floor. For Pavlovian fear conditioning, freezing behavior was recorded during behavioral testing with an infrared activity monitor (Model #: H24-61) that samples movement every 400 milliseconds. The chambers used to assess retention for tone-shock pairings were identical in dimensions to the training apparatus but modified to be contextually different from the conditioning chambers and were located in a different room separate from the laboratory. The conditioning chambers were cleaned with a 10% alcohol solution after training and retention testing. All materials for the behavioral test apparatus were obtained from Coulbourn Instruments (Allentown, PA). The apparatus used for microdialysis collection of norepinephrine from the basolateral amygdala consisted of CMA 120 (Carnegie/Medicin) system for freely moving animals (Height: 360mm, Diameter: 400mm, Material: Perspex). 2.3.1. Microdialysis Novelty Exposure. Animals in Experiment 1 were acclimated to the microdialysis experimental setup for 3 hours each day for five consecutive days (Days 15). The acclimation days familiarized all animals with the microdialysis procedure and involved placing each subject into the CMA collection bowls without disturbance for one hour followed by an additional two

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hours with dummy probes inserted into the microdialysis guide cannulae. On day 6, the day before microdialysis was conducted, animals were randomly assigned to either a preexposed or non-preexposed group. Subjects in the preexposed group were then habituated to the Pavlovian conditioning chamber for 5 minutes while the novelty non-preexposed group remained in the microdialysis bowl. On day 7, animals from both groups were placed in the Pavlovian conditioning chamber for 5 minutes and samples of norepinephrine were collected during exposure and for the next 40 minutes to determine if unfamiliarity or familiarity of a context influences norepinephrine release in the basolateral amygdala. 2.3.2. Fear Conditioning. Rats in Experiments 2 and 3 were transported from the vivarium to the laboratory 1 hour before behavioral testing. One day prior to conditioning, the rats were habituated to the conditioning chamber with 5 minutes of free exploration. Animals assigned to the novelty non-preexposure condition were also transported to the lab but remained in their home cage during the period of habituation for prexposed subjects. Twenty-four hours later, preexposed and non-preexposed subjects were placed in the Pavlovian chamber for conditioning. Three minutes after the rats were in the context, a 30-s tone (5 kHz, 75db) conditioned stimulus (CS) was presented and coterminated with a 1 s, 0.35 mA foot shock unconditioned stimulus (US). A 60 s inter-trial interval separated the foot-shock from the presentation of the next tone Conditioning consisted of five tone-shock pairings. Animals were transported in pairs to a completely different testing room and behavioral chamber to assess memory for the CS tone 48 h following conditioning. Each animal was given an initial 3-minute period of exploration in the new chamber. Afterwards, a CS tone (5 kHz, 75db) was presented for 30 seconds in the absence of the US foot shock. A 30 second inter-trial interval separated the end of one tone and the presentation of the next. Three presentations of the CS tone were given during the retention test. The percentage of time subjects displayed a freezing response during presentation of the CS tone that was previously paired with foot shocks was used as an index of retention.

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2.4. Microdialysis Procedures CMA/12 microdialysis probes were used to collect dialysates from the basolateral amygdala. The probes were perfused continuously during microdialysis experiments with artificial cerebrospinal fluid (aCSF). The microdialysis experiments were divided into 4 phases. The first phase consisted of habituation to the lab for 80 minutes. The next phase was a baseline collection of norepinephrine for 60 minutes. The third phase involved the collection of dialysate samples of norepinephrine during context exposure. Context exposure consisted of animals being placed in the behavioral chamber for 5 min. The final phase of collection was expected to reveal the consequences of a brief context exposure on norepinephrine output in the basolateral amygdala. Dialysate samples of norepinephrine were collected every 20 minutes for 1 hour after animals were exposed to the behavioral chamber. After collection, all samples were stored on ice until they were assayed with high performance liquid chromatography (HPLC).

2.5. Norepinephrine Assay with HPLC Dialysate samples (35 ul) of norepinephrine were assayed by an HPLC system with a Waters 510 pump, Waters 717 autosampler, Atlantis T3 column (3 micron ODS, 4.6 x 100 mm) and a Waters 2465 electrochemical detector. The mobile phase consisted of 50 mg disodium EDTA, 13.8 mg monobasic sodium phosphate and 58 mg octane sulfonate adjusted to pH 3.2 by adding 85% phosphoric acid. The flow rate was adjusted to 1.0 ml per minute.

2.6. Drugs and Infusion Procedures Each rat in Experiment 2 and 3 was restrained by hand in the experimenter’s lap, stylets were removed and 17 mm long, 30-gauge

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injection needles were inserted bilaterally into the basolateral amygdala or central amygdala guide cannulae. The tip of the injection needle extended 2 mm beyond the base of the guide cannulae. The needles were connected to 10 µl Hamilton syringes via PE-20 (polyethylene) tubing. An automated syringe pump (Sage-Orion, Boston, MA) delivered 0.25 µl of PBS or the ß-noradrenergic receptor antagonist propranolol (0.3 µg; Sigma Aldrich, St. Louis, MO) into the basolateral amygdala or central amygdala over a period of 30 s. The injection needles were retained in the guide cannulae for an additional 60 s following infusions to ensure complete delivery of drugs. The stylets were then reinserted into the cannulae. The dose of propranolol given in these studies were selected among those previously shown to attenuate the memory facilitating effects of arousing experimental treatments without impairing memory when given alone (Roozendaal et al., 2006).

2.7. Statistical Analysis Levels (pg/ml) of norepinephrine collected during the three 20 min periods of baseline were averaged to yield a standard baseline value. Comparisons were made between norepinephrine levels at baseline and each 20-minute time point after behavioral training with repeated measures ANOVA. A one-way ANOVA was used to reveal differences in norepinephrine levels at each collection period between the preexposed and novelty non-preexposed groups. Fischer’s post hoc tests were used to analyze specific comparisons between groups. Retention of fear conditioning is expressed as the mean percentage of time  standard errors (SE) rats spent immobile during the presentation of the tone. Between-group comparisons for the freezing behavior measured during retention testing were made with a two-way analysis of variance (ANOVA) followed by Fisher’s post hoc tests. Differences less than p < 0.05 were considered statistically significant.

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2.8. Histology To verify correct placement of injection needle tips and guide cannulae in the basolateral and central nuclei of the amygdala, each animal was anesthetized with the euthanasia solution Euthasol (0.5 ml, Virbac Corporation, Fort Worth, TX) and perfused intracardially with 0.9% saline followed by 10% formalin. The brains were stored in 10% formalin until sectioned on a vibratome. Sections were cut 60 µm thick, mounted on glass slides, subbed with chromium-aluminum and stained with cresyl violet. The location of the cannulae and injection needle tips were verified by examining enlarged projections of the slides (Figure 1).

3. RESULTS 3.1. Experiment 1: Norepinephrine Release in the Basolateral Amygdala Following Exposure to a Novel Environment Study 1 examined whether exposure to a novel context influences norepinephrine output in the basolateral amygdala (Fig. 2). A repeated measures analysis of variance (ANOVA) revealed significantly higher levels of extracellular concentrations of norepinephrine measured from the basolateral nucleus of the amygdala in the novelty non-preexposed group relative to animals that were exposed to the behavioral chamber prior to conducting microdialysis, F (1,21) = 7.115, p < 0.05. Norepinephrine levels measured from the basolateral amygdala of novelty non-preexposed animals was significantly elevated from baseline at all time points following novelty exposure (* p < 0.05; ** p < 0.01). In contrast, changes in norepinephrine levels sampled from the basolateral amygdala of preexposed animals throughout the experiment did not fluctuate from basal values. Post hoc comparisons indicated that extracellular concentrations of norepinephrine measured from non-preexposed animals were significantly greater than animals preexposed to the behavioral chamber at all time

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points throughout the experiment (Non-preexposed vs. Preexposed at 80 min, ¶ p < 0.05; Non-preexposed vs. Preexposed at 100 minutes, ¶ ¶ p < 0.01; Non-preexposed vs. Preexposed at 120 minutes, ¶ ¶ p < 0.01). These findings demonstrate extracellular concentrations of norepinephrine are potentiated in the basolateral amygdala when animals are exposed to a novel context. Moreover, increasing familiarity to a context from preexposure is sufficient to abolish this increase in norepinephrine output within the basolateral amygdala.

Figure 1A. Location of microdialysis cannula placements in the basolateral nucleus of the amygdala (BLA) overlaid onto a representative photomicrograph from animals exposed to the conditioning chamber in Experiment 1. Abbreviations: BLA, Basolateral amygdala nucleus, CEA, Central amygdala nucleus, DG, Dentate gyrus, IC, Internal capsule, LA Lateral amygdala nucleus, PRh, Perirhinal cortex, VPM, Ventral posteromedial thalamic nucleus, 3V, Third ventricle.

Figure 1B. Location of injection cannula placements in the basolateral nucleus of the amygdala (BLA) overlaid onto a representative photomicrograph from animals exposed to the conditioning chamber in Experiment 2. Abbreviations: BLA, Basolateral amygdala nucleus, CEA, Central amygdala nucleus, DG, Dentate gyrus, IC, Internal capsule, LA Lateral amygdala nucleus, PRh, Perirhinal cortex, VPM, Ventral posteromedial thalamic nucleus, 3V, Third ventricle.

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Figure 1C. Location of injection cannula placements in the central nucleus of the amygdala (CEA) overlaid onto a representative photomicrograph from animals trained and tested in Experiment 3. Abbreviations: BLA, Basolateral amygdala nucleus, BMA, Basomedial amygdala nucleus, CEA, Central amygdala nucleus, CPu, Caudate Putamen, DEn, Dorsal endopiriform nucleus, DG, Dentate gyrus, IC, Internal capsule, LA Lateral amygdala nucleus, 3V, Third ventricle.

Figure 2. Exposure to a novel context activates the noradrenergic system in the basolateral nucleus of the amygdala. First exposure to the behavioral chamber produced a significant and sustained increase in extracellular norepinephrine levels relative to baseline for the entire experiment (Behav. Box, 19%, p = ns; 100 min, 27%, * p