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Título: Principles of Neural Science
Autor: Eric Kandel

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Contents:


Front Matter



ChapterDA1-C1)



ChapterDA1-C2)



ChapterDA1-C3)



ChapterDA1-CI)



ChapterDA2-C4)



ChapterDA2-C5)



ChapterDA2-C6)



ChapterDA2-C7)



ChapterDA2-C8)



ChapterDA2-C9)



ChapterDA2-CII)



ChapterDA3-C10)



ChapterDA3-C11)



ChapterDA3-C12)



ChapterDA3-C13)



ChapterDA3-C14)



ChapterDA3-C15)



ChapterDA3-C16)



ChapterDA3-CIII)



ChapterDA4-C17)



ChapterDA4-C18)



ChapterDA4-C19)



ChapterDA4-C20)



ChapterDA4-CIV)



ChapterDA5-C21)



ChapterDA5-C22)



ChapterDA5-C23)



ChapterDA5-C24)



ChapterDA5-C25)



ChapterDA5-C26)



ChapterDA5-C27)



ChapterDA5-C28)



ChapterDA5-C29)



ChapterDA5-C30)



ChapterDA5-C31)



ChapterDA5-C32)



ChapterDA5-CV)



ChapterDA6-C33)



ChapterDA6-C34)



ChapterDA6-C35)



ChapterDA6-C36)



ChapterDA6-C37)



ChapterDA6-C38)



ChapterDA6-C39)



ChapterDA6-C40)



ChapterDA6-C41)



ChapterDA6-C42)



ChapterDA6-C43)



ChapterDA6-CVI)



ChapterDA7-C44)



ChapterDA7-C45)



ChapterDA7-C46)



ChapterDA7-C47)



ChapterDA7-C48)



ChapterDA7-C49)



ChapterDA7-C50)



ChapterDA7-C51)



ChapterDA7-CVII)



ChapterDA8-C52)



ChapterDA8-C53)



ChapterDA8-C54)



ChapterDA8-C55)



ChapterDA8-C56)



ChapterDA8-C57)



ChapterDA8-C58)



ChapterDA8-CVIII)



ChapterDA9-C59)



ChapterDA9-C60)



ChapterDA9-C61)



ChapterDA9-C62)



ChapterDA9-C63)



ChapterDA9-CIX)



Appendices)

Back

Principles of Neural Science
4th_Edition
3
Clinical Medicine
Life Sciences
Neurology
Neuroscience
Text/Reference

Editors
Eric R. Kandel
James H. Schwartz
Thomas M. Jessell
Center for Neurobiology and Behavior, College of Physicians & Surgeons of Columbia University and The Howard Hughes
Medical Institute

Secondary Editors
Sarah Mack
Art Direction
Jane Dodd
Art Direction
John Butler
Editor
Harriet Lebowitz
Editor
Shirley Dahlgren
Production Supervisor
Eve Siegel
Art Manager
Joellen Ackerman
Designer
Judy Cuddihy
Index
Precision Graphics
Illustrators.

R. R. Donnelley & Sons, Inc.
Printer and Binder.

CONTRIBUTORS
David G. Amaral PhD
Professor
Department of Psychiatry, Center for, Neuroscience, University of California, Davis

Allan I. Basbaum PhD
Professor and Chair
Department of Anatomy, University of California, San Francisco; Member W.M., Keck Foundation Center for Integrative

Neuroscience

John C. M. Brust MD
Professor
Department of Neurology, Columbia, University College of Physicians & Surgeons; Director; of Neurology Service, Harlem
Hospital

Linda Buck PhD
Associate Professor
Department of Neurobiology, Harvard Medical School; Associate Investigator, Howard Hughes Medical Institute

Pietro De Camilli MD
Professor and Chairman
Department of Cell Biology, Yale University Medical School

Antonio R. Damasio MD, PhD
M.W. Van Allen Professor and Head
Department of, Neurology, University of Iowa College of Medicine; Adjunct Professor Salk Institute for Biological Studies

Mahlon R. DeLong MD
Professor and Chairman
Department of Neurology, Emory University School of Medicine

Nina F. Dronkers PhD
Chief
Audiology and Speech Pathology VA Northern, California Health Care System; Departments of Neurology and Linguistics,
University of California, Davis

Richard S. J. Frackowiak MD, DSc
Dean
Institute of Neurology, University College, London; Chair, Wellcome Department of Cognitive, Neurology; The National
Hospital for Neurology & Neurosurgery, London

Esther P. Gardner PhD
Professor
Department of Physiology and Neuroscience, New York University School of Medicine

Claude P. J. Ghez MD
Professor
Department of Neurology and Department of Physiology and Cellular Biophysics; Center for Neurobiology and Behavior;
Columbia University, College of Physicians & Surgeons; New York State, Psychiatric Institute

T. Conrad Gilliam PhD
Professor
Department of Genetics and Development, Columbia University College of Physicians & Surgeons

Michael E. Goldberg MD
Chief
Section of Neuro-opthalmological Mechanisms, Laboratory of Sensorimotor Research; National Eye, Institute, National
Institutes of Health

Gary W. Goldstein MD
President
The Kennedy Krieger Research Institute; Professor, Neurology and Pediatrics, The Johns, Hopkins University School of

Medicine

James Gordon EdD
Professor of Practice
Program Director, Physical, Therapy, Graduate School of Health Sciences, New York Medical College

Roger A. Gorski PhD
Professor
Department of Neurobiology, UCLA School of Medicine

A. J. Hudspeth MD, PhD
Professor and Head
Laboratory of Sensory, Neuroscience, Rockefeller University; Investigator, Howard Hughes Medical Institute

Leslie L. Iversen PhD
Professor
Department of Pharmacology, Oxford University

Susan D. Iversen PhD
Professor
Department of Experimental Psychology, Oxford University

Thomas M. Jessell PhD
Professor
Department of Biochemistry and Molecular, Biophysics; Center for Neurobiology and Behavior; Investigator, The Howard
Hughes Medical Institute, Columbia University College of Physicians & Surgeons

Eric R. Kandel MD
University Professor
Departments of Biochemistry and Molecular Biophysics, Physiology and Cellular Biophysics, and Psychiatry; Center for
Neurobiology and Behavior; Senior Investigator, The Howard Hughes, Medical Institute, Columbia University College of
Physicians & Surgeons

John Koester PhD
Professor of Clinical Neurobiology and Behavior in Psychiatry
Acting Director, Center for Neurobiology and Behavior, New York State Psychiatric Institute, Columbia University College of
Physicians & Surgeons

John Krakauer MD
Assistant Professor
Department of Neurology, Columbia University College of Physicians & Surgeons

Irving Kupfermann PhD
Professor
Department of Psychiatry and Department of Physiology and Cellular Biophysics, Center for Neurobiology and Behavior,
Columbia University, College of Physicians & Surgeons

John Laterra MD, PhD
Associate Professor of Neurology
Oncology, and Neuroscience; The Kennedy Krieger Research Institute, Johns Hopkins University School of Medicine

Peter Lennie PhD
Professor of Neural Science
Center for Neural Science, New York University

Gerald E. Loeb MD
Professor
Department of Physiology, Member, MRC, Group in Sensory-Motor Neuroscience, Queen's University, Canada

John H. Martin PhD
Associate Professor
Department of Psychiatry; Center for Neurobiology and Behavior, Columbia University College of Physicians & Surgeons

Geoffrey Melvill Jones MD
Professor
Department of Clinical Neurosciences, Faculty of Medicine, University of Calgary, Canada

Keir Pearson PhD
Professor
Department of Physiology, University of Alberta

Steven Pinker PhD
Professor
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Director, McDonnell-Pew Center for
Cognitive, Neuroscience

Donald L. Price MD
Professor
Neuropathology Laboratory, The Johns, Hopkins University School of Medicine

Allan Rechtshaffen PhD
Professor Emeritus
Department of Psychiatry, and Department of Psychology, University of Chicago

Timothy Roehrs PhD
Director of Research
Henry Ford Sleep Disorders Center

Thomas Roth PhD
Director
, Sleep Disorders and Research Center, Henry, Ford Hospital; University of Michigan

Lewis P. Rowland MD
Professor
Department of Neurology; Columbia, University College of Physicians & Surgeons

Joshua R. Sanes PhD
Professor
Department of Anatomy and Neurobiology; Washington University School of Medicine

Clifford B. Saper MD, PhD
Professor and Chairman
Department of Neurology; Beth Israel Deaconess Medical Center, Harvard, Medical School

James H. Schwartz MD PhD
Professor
Departments of Physiology and Cellular, Biophysics, Neurology and Psychiatry, Center for, Neurobiology and Behavior,

Columbia University, College of Physicians and Surgeons.

Jerome M. Siegel PhD
Professor of Psychiatry
UCLA Medical Center; Chief Neurobiology Research, Sepulveda VA Medical Center

Steven A. Siegelbaum PhD
Professor
Department of Pharmacology, Center for, Neurobiology and Behavior Investigator, Howard, Hughes Medical Institute,
Columbia University, College of Physicians and Surgeons

Marc T. Tessier-Lavigne PhD
Professor
Departments of Anatomy and of, Biochemistry and Biophysics, University of California, San Francisco; Investigator,
Howard Hughes Medical Institute

W. Thomas Thach Jr. MD
Professor
Department of Anatomy and Neurobiology, Washington University School of Medicine

Gary L. Westbrook MD
Senior Scientist and Professor of Neurology
Vollum Institute, Oregon Health Sciences University

Robert H. Wurtz PhD
Chief
Laboratory of Sensorimotor Research, National, Eye Institute; National Institutes of Health

2000
McGraw-Hill
New York
United States of America
0-8385-7701-6

Principles of Neural Science, 4/e
Copyright © 2000 by The McGraw-Hill Companies, Inc. All rights reserved. Printed in the United States of America.
Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or
distributed in any form or by any means, or stored in a data base or retrieval system, without the prior written permission
of the publisher.
Previous edition copyright © 1991 by Appleton & Lange
4567890 DOWDOW 09876543
ISBN 0-8385-7701-6
This book was set in Palatino by Clarinda Prepress, Inc.
This book is printed on acid-free paper.
Cataloging-in-Publication Data is on file for this title at the Library of Congress.

Cover image: The autoradiograph illustrates the widespread localization of mRNA encoding the NMDA-R1 receptor
subtype determined by in situ hybridization. Areas of high NMDA receptor expression are shown as light regions in this
horizontal section of an adult rat brain.

From Moriyoshi K, Masu M, Ishi T, Shigemoto R, Mizuno N, Nakanishi S. 1991. Molecular cloning and characterization of
the rat NMDA receptor. Nature 354:31-37.

Note

Columns II of the Edwin Smith Surgical Papyrus

This papyrus, written in the seventeenth century B.C., contains the earliest reference to the brain anywhere in human
records. According to James Breasted, who translated and published the document in 1930, the word brain

occurs only eight times in ancient Egyptian records, six of them in these pages, which describe the symptoms, diagnosis,
and prognosis of two patients, with compound fractures of the skull. The entire treatise is now in the Rare Book Room of
the New York Academy of Medicine. From James Henry Breasted, 1930. The Edwin Smith Surgical Papyrus, 2 volumes,
Chicago: The University of Chicago Press.
From James Henry Breasted, 1930. The Edwin Smith Surgical Papyrus, 2 volumes, Chicago: The University of Chicago
Press.

Columns IV of the Edwin Smith Surgical Papyrus

Men ought to know that from the brain, and from the brain only, arise our pleasures, joys,
laughter and jests, as well as our sorrows, pains, griefs and tears. Through it, in particular, we
think, see, hear, and distinguish the ugly from the beautiful, the bad from the good, the pleasant
from the unpleasant…. It is the same thing which makes us mad or delirious, inspires us with
dread and fear, whether by night or by day, brings sleeplessness, inopportune mistakes, aimless
anxieties, absent-mindedness, and acts that are contrary to habit. These things that we suffer all
come from the brain, when it is not healthy, but becomes abnormally hot, cold, moist, or dry, or
suffers any other unnatural affection to which it was not accustomed. Madness comes from its
moistness. When the brain is abnormally moist, of necessity it moves, and when it moves neither
sight nor hearing are still, but we see or hear now one thing and now another, and the tongue
speaks in accordance with the things seen and heard on any occasion. But when the brain is still,
a man can think properly.
attributed to Hippocrates Fifth Century, B.C.
From Hippocrates, Vol.2, translated by W.H.S. Jones, London and New York: William Heinemann
and Harvard University Press. 1923.

Notice
Medicine is an ever-changing science. As new research and clinical experience broaden our knowledge, changes in
treatment and drug therapy are required. The editors and the publisher of this work have checked with sources believed to
be reliable in their efforts to provide information that is complete and generally in accord with the standards accepted at
the time of publication. However, in view of the possibility of human error or changes in medical sciences, neither the
editors nor the publisher nor any other party who has been involved in the preparation or publication of this work warrants
that the information contained herein is in every respect accurate or complete, and they are not responsible for any errors
or omissions or for the results obtained from use of such information. Readers are encouraged to confirm the information
contained herein with other sources. For example and in particular, readers are advised to check the product information
sheet included in the package of each drug they plan to administer to be certain that the information contained in this
book is accurate and that changes have not been made in the recommended dose or in the contraindications for
administration. This recommendation is of particular importance in connection with new or infrequently used drugs.

Preface
The goal of neural science is to understand the mind—how we perceive, move, think, and remember. As in the earlier
editions of this book, in this fourth edition we emphasize that behavior can be examined at the level of individual nerve
cells by seeking answers to five basic questions: How does the brain develop? How do nerve cells in the brain
communicate with one another? How do different patterns of interconnections give rise to different perceptions and motor
acts? How is communication between neurons modified by experience? How is that communication altered by diseases?
When we published the first edition of this book in 1981, these questions could be addressed only in cell biological terms.
By the time of the third edition in 1991, however, these same problems were being explored effectively at the molecular
level.
In the eight years intervening between the third and the present edition, molecular biology has continued to facilitate the
analysis of neurobiological problems. Initially molecular biology enriched our understanding of ion channels and receptors
important for signaling. We now have obtained the first molecular structure of an ion channel, providing us with a threedimensional understanding of the ion channel pore. Structural studies also have deepened our understanding of the
membrane receptors coupled to intracellular second-messenger systems and of the role of these systems in modulating
the physiological responses of nerve cells.
Molecular biology also has greatly expanded our understanding of how the brain develops and how it generates behavior.
Characterizations of the genes encoding growth factors and their receptors, transcriptional regulatory factors, and cell and
substrate adhesion molecules have changed the study of neural development from a descriptive discipline into a
mechanistic one. We have even begun to define the molecular mechanisms underlying the developmental processes
responsible for assembling functional neural circuits. These processes include the specification of cell fate, cell migration,
axon growth, target recognition, and synapse formation.
In addition, the ability to develop genetically modified mice has allowed us to relate single genes to signaling in nerve cells
and to relate both of these to an organism's behavior. Ultimately, these experiments will make it possible to study
emotion, perception, learning, memory, and other cognitive processes on both a cellular and a molecular level. Molecular
biology has also made it possible to probe the pathogenesis of many diseases that affect neural function, including several

devastating genetic disorders: muscular dystrophy, retinoblastoma, neurofibromatosis, Huntington disease, and certain
forms of Alzheimer disease.
Finally, the 80,000 genes of the human genome are nearly sequenced. With the possible exception of trauma, every
disease that affects the nervous system has some inherited component. Information about the human genome is making it
possible to identify which genes contribute to these disorders and thus to predict an individual's susceptibility to particular
illnesses. In the long term, finding these genes will radically transform the practice of medicine. Thus we again stress
vigorously our view, advocated since the first edition of this book, that the future of clinical neurology and psychiatry
depends on the progress of molecular neural science.
Advances in molecular neural science have been matched by advances in our understanding of the biology of higher brain
functions. The present-day study of visual perception, emotion, motivation, thought, language, and memory owes much to
the collaboration of cognitive psychology and neural science, a collaboration at the core of the new cognitive neural
science. Not long ago, ascribing a particular aspect of behavior to an unobservable mental process—such as planning a
movement or remembering an event—was thought to be reason for removing the problem from experimental analysis.
Today our ability to visualize functional changes in the brain during normal and abnormal mental activity permits even
complex cognitive processes to be studied directly. No longer are we constrained simply to infer mental functions from
observable behavior. As a result, neural science during the next several decades may develop the tools needed to probe
the deepest of biological mysteries—the biological basis of mind and consciousness.
Despite the growing richness of neural science, we have striven to write a coherent introduction to the nervous system for
students of behavior, biology, and medicine. Indeed, we think this information is even more necessary now than it was
two decades ago. Today neurobiology is central to the biological sciences—students of biology increasingly want to become
familiar with neural science, and more students of psychology are interested in the biological basis of behavior. At the
same time, progress in neural science is providing clearer guidance to clinicians, particularly in the treatment of behavioral
disorders. Therefore we believe it is particularly important to clarify the major principles and mechanisms governing the
functions of the nervous system without becoming lost in details. Thus this book provides the detail necessary to meet the
interests of students in particular fields. It is organized in such a way, however, that excursions into special topics are not
necessary for grasping the major principles of neural science. Toward that end, we have completely redesigned the
illustrations in the book to provide accurate, yet vividly graphic, diagrams that allow the reader to understand the
fundamental concepts of neural science.
With this fourth and millennial edition, we hope to encourage the next generation of undergraduate, graduate, and medical
students to approach the study of behavior in a way that unites its social and its biological dimensions. From ancient
times, understanding human behavior has been central to civilized cultures. Engraved at the entrance to the Temple of
Apollo at Delphi was the famous maxim “Know thyself.” For us, the study of the mind and consciousness defines the
frontier of biology. Throughout this book we both document the central principle that all behavior is an expression of
neural activity and illustrate the insights into behavior that neural science provides.
Eric R. Kandel
James H. Schwartz
Thomas M. Jessell

Acknowledgments
We are again fortunate to have had the creative editorial assistance of Howard Beckman, who read several versions of the
text, demanding clarity of style and logic of argument. We owe a special debt to Sarah Mack, who rethought the whole art
program and converted it to color. With her extraordinary insights into science, she produced remarkably clear diagrams
and figures. In this task, she was aided by our colleague Jane Dodd, who as art editor supervised the program both
scientifically and artistically.
We again owe much to Seta Izmirly: she undertook the demanding task of coordinating the production of this book at
Columbia as she did its predecessor. We thank Harriet Ayers and Millie Pellan, who typed the many versions of the
manuscript; Veronica Winder and Theodore Moallem, who checked the bibliography; Charles Lam, who helped with the art
program; Lalita Hedge who obtained permissions for figures; and Judy Cuddihy, who prepared the index. We also are
indebted to Amanda Suver and Harriet Lebowitz, our development editors, and to the manager of art services, Eve Siegel,
for their help in producing this edition. Finally we want to thank John Butler, for his consistent and thoughtful support of
this project throughout the work on this fourth edition.
Many colleagues have read portions of the manuscript critically. We are especially indebted to John H. Martin for helping
us, once again, with the anatomical drawings. In addition, we thank the following colleagues, who made constructive
comments on various chapters: George Aghajanian, Roger Bannister, Robert Barchi, Cornelia Bargmann, Samuel
Barondes, Elizabeth Bates, Dennis Baylor, Ursula Bellugi, Michael V.L. Bennett, Louis Caplan, Dennis Choi, Patricia
Churchland, Bernard Cohen, Barry Connors, W. Maxwell Cowan, Hanna Damasio, Michael Davis, Vincent Ferrera, Hans

Christian Fibinger, Mark Fishman, Jeff Friedman, Joacquin M. Fuster, Daniel Gardner, Charles Gilbert, Mirchell Glickstein,
Corey Goodman, Jack Gorman, Robert Griggs, Kristen Harris, Allan Hobson, Steven Hyman, Kenneth Johnson, Edward
Jones, John Kalaska, Maria Karayiorgou, Frederic Kass, Doreen Kimura, Donald Klein, Arnold Kriegstein, Robert LaMotte,
Peretz Lavie, Joseph LeDoux, Alan Light, Rodolfo Llinas, Shawn Lockery, John Mann, Eve Marder, C.D. Marsden, Richard
Masland, John Maunsell, Robert Mc-Carley, David McCormick, Chris Miller, George Miller, Adrian Morrison, Thomas Nagel,
William Newsome, Roger Nicoll, Donata Oertel, Richard Palmiter, Michael Posner, V.S. Ramachandran, Elliott Ross, John R.
Searle, Dennis Selkoe, Carla Shatz, David Sparks, Robert Spitzer, Mircea Steriade, Peter Sterling, Larry Swanson, Paula
Tallal, Endel Tulving, Daniel Weinberger, and Michael Young.

Back

1
The Brain and Behavior
Eric R. Kandel
THE LAST FRONTIER OF THE biological sciences—their ultimate challenge—is to understand the biological basis of consciousness and the mental processes by
which we perceive, act, learn, and remember.In the last two decades a remarkable unity has emerged within biology. The ability to sequence genes and infer the
amino acid sequences for the proteins they encode has revealed unanticipated similarities between proteins in the nervous system and those encountered
elsewhere in the body. As a result, it has become possible to establish a general plan for the function of cells, a plan that provides a common conceptual
framework for all of cell biology, including cellular neurobiology. The next and even more challenging step in this unifying process within biology, which we outline
in this book, will be the unification of the study of behavior—the science of the mind—and neural science, the science of the brain. This last step will allow us to
achieve a unified scientific approach to the study of behavior.
Such a comprehensive approach depends on the view that all behavior is the result of brain function. What we commonly call the mind is a set of operations
carried out by the brain. The actions of the brain underlie not only relatively simple motor behaviors such as walking or eating, but all the complex cognitive
actions that we believe are quintessentially human, such as thinking, speaking, and creating works of art. As a corollary, all the behavioral disorders that
characterize psychiatric illness—disorders of affect (feeling) and cognition (thought)—are disturbances of brain function.
The task of neural science is to explain behavior in terms of the activities of the brain. How does the brain marshal its millions of individual nerve cells to produce
behavior, and how are these cells influenced by the environment, which includes the actions of other people? The progress of neural science in explaining human
behavior is a major theme of this book.
Like all science, neural science must continually confront certain fundamental questions. Are particular mental processes localized to specific regions of the brain,
or does the mind represent a collective and emergent property of the whole brain? If specific mental processes can be localized to discrete brain regions, what is
the relationship between the anatomy and physiology of one region and its specific function in perception, thought, or movement? Are such relationships more
likely to be revealed by examining the region as a whole or by studying its individual nerve cells? In this chapter we consider to what degree mental functions are
located in specific regions of the brain and to what degree such local mental processes can be understood in terms of the properties of specific nerve cells and
their interconnections.
To answer these questions, we look at how modern neural science approaches one of the most elaborate cognitive behaviors—language. In doing so we
necessarily
P.6
focus on the cerebral cortex, the part of the brain concerned with the most evolved human behaviors. Here we see how the brain is organized into regions or
brain compartments, each made up of large groups of neurons, and how highly complex behaviors can be traced to specific regions of the brain and understood
in terms of the functioning of groups of neurons. In the next chapter we consider how these neural circuits function at the cellular level, using a simple reflex
behavior to examine the way sensory signals are transformed into motor acts.

Two Opposing Views Have Been Advanced on the Relationship Between Brain and Behavior
Our current views about nerve cells, the brain, and behavior have emerged over the last century from a convergence of five experimental traditions: anatomy,
embryology, physiology, pharmacology, and psychology.
Before the invention of the compound microscope in the eighteenth century, nervous tissue was thought to function like a gland—an idea that goes back to the
Greek physician Galen, who proposed that nerves convey fluid secreted by the brain and spinal cord to the body's periphery. The microscope revealed the true
structure of the cells of nervous tissue. Even so, nervous tissue did not become the subject of a special science until the late 1800s, when the first detailed
descriptions of nerve cells were undertaken by Camillo Golgi and Santiago Ramón y Cajal.
Golgi developed a way of staining neurons with silver salts that revealed their entire structure under the microscope. He could see clearly that neurons had cell
bodies and two major types of projections or processes: branching dendrites at one end and a long cable-like axon at the other. Using Golgi's technique, Ramón y
Cajal was able to stain individual cells, thus showing that nervous tissue is not one continuous web but a network of discrete cells. In the course of this work,
Ramón y Cajal developed some of the key concepts and much of the early evidence for the neuron doctrine—the principle that individual neurons are the
elementary signaling elements of the nervous system.
Additional experimental support for the neuron doctrine was provided in the 1920s by the American embryologist Ross Harrison, who demonstrated that the two
major projections of the nerve cell—the dendrites and the axon—grow out from the cell body and that they do so even in tissue culture in which each neuron is
isolated from other neurons. Harrison also confirmed Ramón y Cajal's suggestion that the tip of the axon gives rise to an expansion called the growth cone, which
leads the developing axon to its target (whether to other nerve cells or to muscles).
Physiological investigation of the nervous system began in the late 1700s when the Italian physician and physicist Luigi Galvani discovered that living excitable
muscle and nerve cells produce electricity. Modern electrophysiology grew out of work in the nineteenth century by three German physiologists—Emil DuBoisReymond, Johannes Müller, and Hermann von Helmholtz—who were able to show that the electrical activity of one nerve cell affects the activity of an adjacent
cell in predictable ways.
Pharmacology made its first impact on our understanding of the nervous system and behavior at the end of the nineteenth century, when Claude Bernard in
France, Paul Ehrlich in Germany, and John Langley in England demonstrated that drugs do not interact with cells arbitrarily, but rather bind to specific receptors
typically located in the membrane on the cell surface. This discovery became the basis of the all-important study of the chemical basis of communication between
nerve cells.
The psychological investigation of behavior dates back to the beginnings of Western science, to classical Greek philosophy. Many issues central to the modern
investigation of behavior, particularly in the area of perception, were subsequently reformulated in the seventeenth century first by René Descartes and then by
John Locke, of whom we shall learn more later. In the midnineteenth century Charles Darwin set the stage for the study of animals as models of human actions
and behavior by publishing his observations on the continuity of species in evolution. This new approach gave rise to ethology, the study of animal behavior in
the natural environment, and later to experimental psychology, the study of human and animal behavior under controlled conditions.
In fact, by as early as the end of the eighteenth century the first attempts had been made to bring together biological and psychological concepts in the study of
behavior. Franz Joseph Gall, a German physician and neuroanatomist, proposed three radical new ideas. First, he advocated that all behavior emanated from the
brain. Second, he argued that particular regions of the cerebral cortex controlled specific functions. Gall asserted that the cerebral cortex did not act as a single
organ but was divided into at least 35 organs (others were added later), each corresponding to a specific mental faculty. Even the most abstract of human
behaviors, such as generosity, secretiveness, and religiosity were assigned their spot in the brain. Third, Gall proposed that the center for each mental function
grew with use, much as a muscle bulks up with exercise. As each center
P.7

grew, it purportedly caused the overlying skull to bulge, creating a pattern of bumps and ridges on the skull that indicated which brain regions were most
developed (Figure 1-1). Rather than looking within the brain, Gall sought to establish an anatomical basis for describing character traits by correlating the
personality of individuals with the bumps on their skulls. His psychology, based on the distribution of bumps on the outside of the head, became known as
phrenology.
In the late 1820s Gall's ideas were subjected to experimental analysis by the French physiologist Pierre Flourens. By systematically removing Gall's functional
centers from the brains of experimental animals, Flourens attempted to isolate the contributions of each “cerebral organ” to behavior. From these experiments he
concluded that specific brain regions were not responsible for specific behaviors, but that all brain regions, especially the cerebral hemispheres of the forebrain,
participated in every mental operation. Any part of the cerebral hemisphere, he proposed, was able to perform all the functions of the hemisphere. Injury to a
specific area of the cerebral hemisphere would therefore affect all higher functions equally.
In 1823 Flourens wrote: “All perceptions, all volitions occupy the same seat in these cerebral) organs; the faculty of perceiving, of conceiving, of willing merely
constitutes therefore a faculty which is essentially one.” The rapid acceptance of this belief (later called the aggregate-field view of the brain) was based only
partly on Flourens's experimental work. It also represented a cultural reaction against the reductionist view that the human mind has a biological basis, the
notion that there was no soul, that all mental processes could be reduced to actions within different regions in the brain!
The aggregate-field view was first seriously challenged in the mid-nineteenth century by the British neurologist J. Hughlings Jackson. In his studies of focal
epilepsy, a disease characterized by convulsions that begin in a particular part of the body, Jackson showed that different motor and sensory functions can be
traced to different parts of the cerebral cortex. These studies were later refined by the German neurologist Karl Wernicke, the English physiologist Charles
Sherrington, and Ramón y Cajal into a view of brain function called cellular connectionism. According to this view, individual neurons are the signaling units of the
brain; they are generally arranged in functional groups and connect to one another in a precise fashion. Wernicke's work in particular showed that different
behaviors are produced by different brain regions interconnected by specific neural pathways.
The differences between the aggregate-field theory and cellular-connectionism can best be illustrated by an analysis of how the brain produces language. Before
we consider the relevant clinical and anatomical studies concerned with the localization of language, let us briefly look at the overall structure of the brain. (The
anatomical organization of the nervous system is described in detail in Chapter 17.)

Figure 1-1 According to the nineteenth-century doctrine of phrenology, complex traits such as combativeness, spirituality, hope, and
conscientiousness are controlled by specific areas in the brain, which expand as the traits develop. This enlargement of local areas of the brain was
thought to produce characteristic bumps and ridges on the overlying skull, from which an individual's character could be determined. This map, taken from a
drawing of the early 1800s, purports to show 35 intellectual and emotional faculties in distinct areas of the skull and the cerebral cortex underneath.

The Brain Has Distinct Functional Regions
The central nervous system is a bilateral and essentially symmetrical structure with seven main parts: the spinal cord, medulla oblongata, pons, cerebellum,
midbrain, diencephalon, and the cerebral hemispheres (Box 1-1 and Figures 1-2A,1-2B and 1-3). Radiographic imaging techniques have made it possible to
visualize these structures in living subjects. Through a variety of experimental methods, such images of the brain can be made while subjects are engaged in
specific tasks, which then can be related to the activities of discrete regions of the brain. As a result, Gall's original idea that different regions are
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specialized for different functions is now accepted as one of the cornerstones of modern brain science.

Box 1-1 The Central Nervous System
The central nervous system has seven main parts (Figure 1-2A).



The spinal cord, the most caudal part of the central nervous system, receives and processes sensory information from the skin, joints, and muscles
of the limbs and trunk and controls movement of the limbs and the trunk. It is subdivided into cervical, thoracic, lumbar, and sacral regions. The
spinal cord continues rostrally as the brain stem, which consists of the medulla, pons, and midbrain (see below). The brain stem receives sensory
information from the skin and muscles of the head and provides the motor control for the muscles of the head. It also conveys information from the
spinal cord to the brain and from the brain to the spinal cord, and regulates levels of arousal and awareness, through the reticular formation. The
brain stem contains several collections of cell bodies, the cranial nerve nuclei. Some of these nuclei receive information from the skin and muscles of

the head; others control motor output to muscles of the face, neck, and eyes. Still others are specialized for information from the special senses:
hearing, balance, and taste.


The medulla oblongata, which lies directly above the spinal cord, includes several centers responsible for vital autonomic functions, such as
digestion, breathing, and the control of heart rate.


The pons, which lies above the medulla, conveys information about movement from the cerebral hemisphere to the cerebellum.


The cerebellum lies behind the pons and is connected to the brain stem by several major fiber tracts called peduncles. The cerebellum modulates
the force and range of movement and is involved in the learning of motor skills.

Figure 1-2A The central nervous system can be divided into seven main parts.



The midbrain, which lies rostral to the pons, controls many sensory and motor functions, including eye movement and the coordination of visual and
auditory reflexes.


The diencephalon lies rostral to the midbrain and contains two structures. One, the thalamus, processes most of the information reaching the
cerebral cortex from the rest of the central nervous system. The other, the hypothalamus, regulates autonomic, endocrine, and visceral function.


The cerebral hemispheres consist of a heavily wrinkled outer layer—the cerebral cortex —and three deep-lying structures: the basal ganglia, the
hippocampus, and the amygdaloid nuclei. The basal ganglia participate in regulating motor performance; the hippocampus is involved with aspects of
memory storage; and the amygdaloid nuclei coordinate the autonomic and endocrine responses of emotional states. The cerebral cortex is divided
into four lobes: frontal, parietal, temporal, and occipital (Figure 1-2B).

The brain is also commonly divided into three broader regions: the hindbrain (the medulla, pons, and cerebellum), midbrain, and forebrain (diencephalon
and cerebral hemispheres). The hindbrain (excluding the cerebellum) and midbrain comprise the brain stem.

Figure 1-2B The four lobes of the cerebral cortex.

Figure 1-3 The main divisions are clearly visible when the brain is cut down the midline between the two hemispheres.
A. This schematic drawing shows the position of major structures of the brain in relation to external landmarks. Students of brain anatomy quickly learn to
distinguish the major internal landmarks, such as the corpus callosum, a large bundle of nerve fibers that connects the left and right hemispheres.
B. The major brain divisions drawn in A are also evident here in a magnetic resonance image of a living human brain.

One reason this conclusion eluded investigators for so many years lies in another organizational principle of the nervous system known as parallel distributed
processing. As we shall see below, many sensory, motor, and cognitive functions are served by more than one neural pathway. When one functional region or
pathway is damaged, others may be able to compensate partially for the loss, thereby obscuring the behavioral evidence for localization. Nevertheless, the neural
pathways for certain higher functions have been precisely mapped in the brain.

Cognitive Functions Are Localized Within the Cerebral Cortex
The brain operations responsible for our cognitive abilities occur primarily in the cerebral cortex —the furrowed gray matter covering the cerebral hemispheres. In
each of the brain's two hemispheres the overlying cortex is divided into four anatomically distinct lobes: frontal, parietal, temporal, and occipital (see Figure 12B), originally named for the skull bones that encase them. These lobes have specialized functions. The frontal lobe is largely concerned with planning future
action and with the control of movement; the parietal lobe with somatic sensation, with forming a body image, and with relating one's body image with
extrapersonal space; the occipital lobe with vision; the temporal lobe with hearing; and through its deep structures—the hippocampus and the amygdaloid
nuclei—with aspects of learning, memory, and emotion. Each lobe has several characteristic deep infoldings (a favored evolutionary strategy for packing in more
cells in a limited space). The crests of these convolutions are called gyri, while the intervening grooves are called sulci or fissures. The more prominent gyri and
sulci are quite similar in everyone and have specific names. For example, the central sulcus separates the precentral gyrus, which is concerned with motor
function, from the postcentral gyrus, which is concerned with sensory function (Figure 1-4A).
The organization of the cerebral cortex is characterized by two important features. First, each hemisphere is concerned primarily with sensory and motor
processes on the contralateral (opposite) side of the body. Thus sensory information that arrives at the spinal cord from the left side of the body—from the left
hand, say—crosses over to the right side of the nervous system (either within the spinal cord or in the brain stem) on its way to the cerebral cortex. Similarly,
the motor areas in the right hemisphere exert control over the movements of the left half
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of the body. Second, although the hemispheres are similar in appearance, they are not completely symmetrical in structure nor equivalent in function.
To illustrate the role of the cerebral cortex in cognition, we will trace the development of our understanding of the neural basis of language, using it as an
example of how we have progressed in localizing mental functions in the brain. The neural basis of language is discussed more fully in Chapter 59.
Much of what we know about the localization of language comes from studies of aphasia, a language disorder found most often in patients who have suffered a
stroke (the occlusion or rupture of a blood vessel supplying blood to a portion of the cerebral hemisphere). Many of the important discoveries in the study of
aphasia occurred in rapid succession during the last half of the nineteenth century. Taken together, these advances form one of the most exciting chapters in the
study of human behavior, because they offered the first insight into the biological basis of a complex mental function.
The French neurologist Pierre Paul Broca was much influenced by Gall and by the idea that functions could be localized. But he extended Gall's thinking in an
important way. He argued that phrenology, the attempt to localize the functions of the mind, should be based on examining damage to the brain produced by
clinical lesions rather than by examining the distribution of bumps on the outside of the head. Thus he wrote in 1861: “I had thought that if there were ever a
phrenological science, it would be the phrenology of convolutions (in the cortex), and not the phrenology of bumps (on the head).” Based on this insight Broca
founded neuropsychology, a new science of mental processes that he was to distinguish from the phrenology of Gall.
In 1861 Broca described a patient named Leborgne, who could understand language but could not speak. The patient had none of the conventional motor deficits
(of the tongue, mouth, or vocal cords) that would affect speech. In fact, he could utter isolated words, whistle, and sing a melody without difficulty. But he could
not speak grammatically or create complete sentences, nor could he express ideas in writing. Postmortem examination of this patient's brain showed a lesion in
the posterior region of the frontal lobe (now called Broca's area; Figure 1-4B). Broca studied eight similar patients, all with lesions in this region, and in each case
found that the lesion was located in the left cerebral hemisphere. This discovery led Broca to announce in 1864 one of the most famous principles of brain
function: “Nous parlons avec l'hémisphère gauche!” (“We speak with the left hemisphere!”)
Broca's work stimulated a search for the cortical sites of other specific behavioral functions—a search soon rewarded. In 1870 Gustav Fritsch and Eduard Hitzig
galvanized the scientific community by showing that characteristic and discrete limb movements in dogs, such as extending a paw, can be produced by
electrically stimulating a localized region of the precentral gyrus of the brain. These discrete regions were invariably located in the contralateral motor cortex.
Thus, the right hand, the one most humans use for writing and skilled movements, is controlled by the left hemisphere, the same hemisphere that controls
speech. In most people, therefore, the left hemisphere is regarded as dominant.

Figure 1-4 The major areas of the cerebral cortex are shown in this lateral view of the of the left hemisphere.
A. Outline of the left hemisphere.
B. Areas involved in language. Wernicke's area processes the auditory input for language and is important to the understanding of speech. It lies near the
primary auditory cortex and the angular gyrus, which combines auditory input with information from other senses. Broca's area controls the production of
intelligible speech. It lies near the region of the motor area that controls the mouth and tongue movements that form words. Wernicke's area communicates
with Broca's area by a bidirectional pathway, part of which is made up of the arcuate fasciculus. (Adapted from Geschwind 1979.)

The next step was taken in 1876 by Karl Wernicke. At age 26 Wernicke published a now classic paper, “The
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Symptom-Complex of Aphasia: APsychological Study on an Anatomical Basis.” In it he described another type of aphasia, one involving a failure to comprehend
language rather than to speak (a receptive as opposed to an expressive malfunction). Whereas Broca's patients could understand language but not speak,
Wernicke's patient could speak but could not understand language. Moreover, the locus of this new type of aphasia was different from that described by Broca:
the critical cortical lesion was located in the posterior part of the temporal lobe where it joins the parietal and occipital lobes (Figure 1-4B).
On the basis of this discovery, and the work of Broca, Fritsch, and Hitzig, Wernicke formulated a theory of language that attempted to reconcile and extend the
two theories of brain function holding sway at that time. Phrenologists argued that the cortex was a mosaic of functionally specific areas, whereas the aggregatefield school argued that mental functions were distributed homogeneously throughout the cerebral cortex. Wernicke proposed that only the most basic mental
functions, those concerned with simple perceptual and motor activities, are localized to single areas of the cortex. More complex cognitive functions, he argued,
result from interconnections between several functional sites. In placing the principle of localized function within a connectionist framework, Wernicke appreciated
that different components of a single behavior are processed in different regions of the brain. He was thus the first to advance the idea of distributed processing,
now central to our understanding of brain function.
Wernicke postulated that language involves separate motor and sensory programs, each governed by separate cortical regions. He proposed that the motor
program, which governs the mouth movements for speech, is located in Broca's area, suitably situated in front of the motor area that controls the mouth,
tongue, palate, and vocal cords (Figure 1-4B). And he assigned the sensory program, which governs word perception, to the temporal lobe area he discovered
(now called Wernicke's area). This area is conveniently surrounded by the auditory cortex as well as by areas collectively known as association cortex, areas that
integrate auditory, visual, and somatic sensation into complex perceptions.
Thus Wernicke formulated the first coherent model for language organization that (with modifications and elaborations we shall soon learn about) is still of some
use today. According to this model, the initial steps in the processing of spoken or written words by the brain occur in separate sensory areas of the cortex
specialized for auditory or visual information. This information is then conveyed to a cortical association area specialized for both visual and auditory information,
the angular gyrus. Here, according to Wernicke, spoken or written words are transformed into a common neural representation shared by both speech and
writing. From the angular gyrus this representation is conveyed to Wernicke's area, where it is recognized as language and associated with meaning. Without that
association, the ability to comprehend language is lost. The common neural representation is then relayed from Wernicke's to Broca's area, where it is
transformed from a sensory (auditory or visual) representation into a motor representation that can potentially lead to spoken or written language. When the laststage transformation from sensory to motor representation cannot take place, the ability to express language (either as spoken words or in writing) is lost.
Based on this premise, Wernicke correctly predicted the existence of a third type of aphasia, one that results from disconnection. Here the receptive and motor
speech zones themselves are spared but the neuronal fiber pathways that connect them are destroyed. This conduction aphasia, as it is now called, is
characterized by an incorrect use of words (paraphasia). Patients with conduction aphasia understand words that they hear and read and have no motor
difficulties when they speak. Yet they cannot speak coherently; they omit parts of words or substitute incorrect sounds. Painfully aware of their own errors, they
are unable to put them right.
Inspired in part by Wernicke, a new school of cortical localization arose in Germany at the beginning of the twentieth century led by the anatomist Korbinian
Brodmann. This school sought to distinguish different functional areas of the cortex based on variations in the structure of cells and in the characteristic
arrangement of these cells into layers. Using this cytoarchitectonic method, Brodmann distinguished 52 anatomically and functionally distinct areas in the human
cerebral cortex (Figure 1-5).
Thus, by the beginning of the twentieth century there was compelling biological evidence for many discrete areas in the cortex, some with specialized roles in

behavior. Yet during the first half of this century the aggregate-field view of the brain, not cellular connectionism, continued to dominate experimental thinking
and clinical practice. This surprising state of affairs owed much to the arguments of several prominent neural scientists, among them the British neurologist
Henry Head, the German neuropsychologist Kurt Goldstein, the Russian behavioral physiologist Ivan Pavlov, and the American psychologist Karl Lashley, all
advocates of the aggregate-field view.
The most influential of this group was Lashley, who was deeply skeptical of the cytoarchitectonic approach to functional delineation of the cortex. “The ‘ideal’
architectonic map is nearly worthless,” Lashley wrote.
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“The area subdivisions are in large part anatomically meaningless, and misleading as to the presumptive functional divisions of the cortex.” Lashley's skepticism
was reinforced by his attempts, in the tradition of Flourens's work, to find a specific seat of learning by studying the effects of various brain lesions on the ability
of rats to learn to run a maze. But Lashley found that the severity of the learning defect seemed to depend on the size of the lesions, not on their precise site.
Disillusioned, Lashley—and, after him, many other psychologists —concluded that learning and other mental functions have no special locus in the brain and
consequently cannot be pinned down to specific collections of neurons.
On the basis of his observations, Lashley reformulated the aggregate-field view into a theory of brain function called mass action, which further belittled the
importance of individual neurons, specific neuronal connections, and brain regions dedicated to particular tasks. According to this view, it was brain mass, not its
neuronal components, that was crucial to its function. Applying this logic to aphasia, Head and Goldstein asserted that language disorders could result from injury
to almost any cortical area. Cortical damage, regardless of site, caused patients to regress from a rich, abstract language to the impoverished utterances of
aphasia.
Lashley's experiments with rats, and Head's observations on human patients, have gradually been reinterpreted. A variety of studies have demonstrated that the
maze-learning task used by Lashley is unsuited to the study of local cortical function because the task involves so many motor and sensory capabilities. Deprived
of one sensory capability (such as vision), a rat can still learn to run a maze using another (by following tactile or olfactory cues). Besides, as we shall see, many
mental functions are handled by more than one region or neuronal pathway, and a single lesion may not eliminate them all.
In addition, the evidence for the localization of function soon became overwhelming. Beginning in the late 1930s, Edgar Adrian in England and Wade Marshall and
Philip Bard in the United States discovered that applying a tactile stimulus to different parts of a cat's body elicits electrical activity in distinctly different
subregions of the cortex, allowing for the establishment of a precise map of the body surface in specific areas of the cerebral cortex described by Brodmann.
These studies established that cytoarchitectonic areas of cortex can be defined unambiguously according to several independent criteria, such as cell type and cell
layering, connections, and—most important—physiological function. As we shall see in later chapters, local functional specialization has emerged as a key
principle of cortical organization, extending even to individual columns of cells within a functional area. Indeed, the brain is divided into many more functional
regions than even Brodmann envisaged!

Figure 1-5 In the early part of the twentieth century Korbinian Brodmann divided the human cerebral cortex into 52 discrete areas on the basis
of distinctive nerve cell structures and characteristic arrangements of cell layers. Brodmann's scheme of the cortex is still widely used today and is
continually updated. In this drawing each area is represented by its own symbol and is assigned a unique number. Several areas defined by Brodmann have
been found to control specific brain functions. For instance, area 4, the motor cortex, is responsible for voluntary movement. Areas 1, 2, and 3 comprise the
primary somatosensory cortex, which receives information on bodily sensation. Area 17 is the primary visual cortex, which receives signals from the eyes and
relays them to other areas for further deciphering. Areas 41 and 42 comprise the primary auditory cortex. Areas not visible from the outer surface of the cortex
are not shown in this drawing.

More refined methods have made it possible to learn even more about the function of different brain regions involved in language. In the late 1950s Wilder
Penfield, and more recently George Ojemann used small electrodes to stimulate the cortex of awake patients during brain surgery for epilepsy (carried out under
local anesthesia), in search of areas that produce language. Patients were asked to name objects or use language in other ways while different areas of the
cortex were stimulated. If the area of the cortex was critical for language, application of the electrical stimulus blocked the patient's ability to name objects. In
this way Penfield and Ojemann were able to confirm—in the living conscious brain—the language areas of the cortex described by Broca and Wernicke. In
addition, Ojemann discovered other sites essential for language, indicating
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that the neural networks for language are larger than those delineated by Broca and Wernicke.
Our understanding of the neural basis of language has also advanced through brain localization studies that combine linguistic and cognitive psychological
approaches. From these studies we have learned that a brain area dedicated to even a specific component of language, such as Wernicke's area for language
comprehension, is further subdivided functionally. These modular subdivisions of what had previously appeared to be fairly elementary operations were first
discovered in the mid 1970s by Alfonso Caramazza and Edgar Zurif. They found that different lesions within Wernicke's area give rise to different failures to
comprehend. Lesions of the frontal-temporal region of Wernicke's area result in failures in lexical processing, an inability to understand the meaning of words. By
contrast, lesions in the parietal-temporal region of Wernicke's area result in failures in syntactical processing, the ability to understand the relationship between
the words of a sentence. (Thus syntactical knowledge allows one to appreciate that the sentence “Jim is in love with Harriet” has a different meaning from
“Harriet is in love with Jim.”)
Until recently, almost everything we knew about the anatomical organization of language came from studies of patients who had suffered brain lesions. Positron
emission tomography (PET) and functional magnetic resonance imaging (MRI) have extended this approach to normal people (Chapter 20). PET is a noninvasive
imaging technique for visualizing the local changes in cerebral blood flow and metabolism that accompany mental activities, such as reading, speaking, and
thinking. In 1988, using this new imaging form, Michael Posner, Marcus Raichle, and their colleagues made an interesting discovery. They found that the

incoming sensory information that leads to language production and understanding is processed in more than one pathway.
Recall that Wernicke believed that both written and spoken words are transformed into a representation of language by both auditory and visual inputs. This
information, he thought, is then conveyed to Wernicke's area, where it becomes associated with meaning before being transformed in Broca's area into output as
spoken language. Posner and his colleagues asked: Must the neural code for a word that is read be translated into an auditory representation before it can be
associated with a meaning? Or can visual information be sent directly to Broca's area with no involvement of the auditory system? Using PET, they determined
how individual words are coded in the brain of normal subjects when the words are read on a screen or heard through earphones. Thus, when words are heard
Wernicke's area becomes active, but when words are seen but not heard or spoken Wernicke's area is not activated. The visual information from the occipital
cortex appears to be conveyed directly to Broca's area without first being transformed into an auditory representation in the posterior temporal cortex. Posner
and his colleagues concluded that the brain pathways and sensory codes used to see words are different from those used to hear words. They proposed,
therefore, that these pathways have independent access to higher-order regions of the cortex concerned with the meaning of words and with the ability to
express language (Figure 1-6).
Not only are reading and listening processed separately, but the act of thinking about a word's meaning (in the absence of sensory inputs) activates a still
different area in the left frontal cortex. Thus language processing is parallel as well as serial; as we shall learn in Chapter 59, it is considerably more complex
than initially envisaged by Wernicke. Indeed, similar conclusions have been reached from studies of behavior other than language. These studies demonstrate
that information processing requires many individual cortical areas that are appropriately interconnected—each of them responding to, and therefore coding for,
only some aspects of specific sensory stimuli or motor movement, and not for others.
Studies of aphasia afford unusual insight into how the brain is organized for language. One of the most impressive insights comes from a study of deaf people
who lost their ability to speak American Sign Language after suffering cerebral damage. Unlike spoken language, American signing is accomplished with hand
gestures rather than by sound and is perceived by visual rather than auditory pathways. Nonetheless, signing, which has the same structural complexities
characteristic of spoken languages, is also localized to the left hemisphere. Thus, deaf people can become aphasic for sign language as a result of lesions in the
left hemisphere. Lesions in the right hemisphere do not produce these defects. Moreover, damage to the left hemisphere can have quite specific consequences,
affecting either sign comprehension (following damage in Wernicke's area) or grammar (following damage in Broca's area) or signing fluency.
These observations illustrate three points. First, the cognitive processing for language occurs in the left hemisphere and is independent of pathways that process
the sensory or motor modalities used in language. Second, speech and hearing are not necessary conditions for the emergence of language capabilities in the left
hemisphere. Third, spoken language represents only one of a family of cognitive skills mediated by the left hemisphere.

Figure 1-6 Specific regions of the cortex involved in the recognition of a spoken or written word can be identified with PET scanning. Each of the
four images of the human brain shown here (from the left side of the cortex) actually represents the averaged brain activity of several normal subjects. (In
these PET images white represents the areas of highest activity, red and yellow quite high activity, and blue and gray the areas of minimal activity.) The “input”
component of language (reading or hearing a word) activates the regions of the brain shown in A and B. The motor “output” component of language (speech or
thought) activates the regions shown in C and D. (Courtesy of Cathy Price.)
A. The reading of a single word produces a response both inthe primary visual cortex and in the visual association cortex (see Figure 1-5).
B. Hearing a word activates an entirely different set of areas in the temporal cortex and at the junction of the temporalparietal cortex. (To control for irrelevant
differences, the same list of words was used in both the reading and listening tests.) A and B show that the brain uses several discrete pathways for processing
language and does not transform visual signals for processing in the auditory pathway.
C. Subjects were asked to repeat a word presented either through earphones or on a screen. Speaking a word activates the supplementary motor area of the
medial frontal cortex. Broca's area is activated whether the word is presented orally or visually. Thus both visual and auditory pathways converge on Broca's
area, the common site for the motor articulation of speech.
D. Subjects were asked to respond to the word “brain” with an appropriate verb (for example, “to think”). This type of thinking activates the frontal cortex as
well as Broca's and Wernicke's areas. These areas play a role in all cognition and abstract representation.

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Affective Traits and Aspects of Personality Are Also Anatomically Localized
Despite the persuasive evidence for localized languagerelated functions in the cortex, the idea nevertheless persisted that affective (emotional) functions are not
localized. Emotion, it was believed, must be an expression of whole-brain activity. Only recently has this view been modified. Although the emotional aspects of
behavior have not been as precisely mapped as sensory, motor, and cognitive functions, distinct emotions can be elicited by stimulating specific parts of the brain
in humans or experimental animals. The localization of affect has been dramatically demonstrated in patients with certain language disorders and those with a
particular type of epilepsy.
Aphasia patients not only manifest cognitive defects in language, but also have trouble with the affective aspects of language, such as intonation (or prosody).
These affective aspects are represented in the right
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hemisphere and, rather strikingly, the neural organization of the affective elements of language mirrors the organization of the logical content of language in the
left hemisphere. Damage to the right temporal area corresponding to Wernicke's area in the left temporal region leads to disturbances in comprehending the
emotional quality of language, for example, appreciating from a person's tone of voice whether he is describing a sad or happy event. In contrast, damage to the
right frontal area corresponding to Broca's area leads to difficulty in expressing emotional aspects of language.
Thus some linguistic functions also exist in the right hemisphere. Indeed, there is now considerable evidence that an intact right hemisphere may be necessary to
an appreciation of subtleties of language, such as irony, metaphor, and wit, as well as the emotional content of speech. Certain disorders of affective language
that are localized to the right hemisphere, called aprosodias, are classified as sensory, motor, or conduction aprosodias, following the classification used for
aphasias. This pattern of localization appears to be inborn, but it is by no means completely determined until the age of about seven or eight. Young children in
whom the left cerebral hemisphere is severely damaged early in life can still develop an essentially normal grasp of language.
Further clues to the localization of affect come from patients with chronic temporal lobe epilepsy. These patients manifest characteristic emotional changes, some
of which occur only fleetingly during the seizure itself and are called ictal phenomena (Latin ictus, a blow or a strike). Common ictal phenomena include feelings
of unreality and déjàvu (the sensation of having been in a place before or of having had a particular experience before); transient visual or auditory
hallucinations; feelings of depersonalization, fear, or anger; delusions; sexual feelings; and paranoia.
More enduring emotional changes, however, are evident when patients are not having seizures. These interictal phenomena are interesting because they
represent a true psychiatric syndrome. A detailed study of such patients indicates they lose all interest in sex, and the decline in sexual interest is often paralleled
by a rise in social aggressiveness. Most exhibit one or more distinctive personality traits: They can be intensely emotional, ardently religious, extremely
moralistic, and totally lacking in humor. In striking contrast, patients with epileptic foci outside the temporal lobe show no abnormal emotion and behavior.
One important structure for the expression and perception of emotion is the amygdala, which lies deep within the cerebral hemispheres. The role of this structure
in emotion was discovered through studies of the effects of the irritative lesions of epilepsy within the temporal lobe. The consequences of such irritative lesions
are exactly the opposite of those of destructive lesions resulting from a stroke or injury. Whereas destructive lesions bring about loss of function, often through
the disconnection of specialized areas, the electrical storm of epilepsy can increase activity in the regions affected, leading to excessive expression of emotion or
over-elaboration of ideas. We consider the neurobiology of emotion in Part VIII of this book.

Mental Processes Are Represented in the Brain by Their Elementary Processing Operations
Why has the evidence for localization, which seems so obvious and compelling in retrospect, been rejected so often in the past? The reasons are several.
First, phrenologists introduced the idea of localization in an exaggerated form and without adequate evidence. They imagined each region of the cerebral cortex
as an independent mental organ dedicated to a complete and distinct mental function (much as the pancreas and the liver are independent digestive organs).
Flourens's rejection of phrenology and the ensuing dialectic between proponents of the aggregate-field view (against localization) and the cellular connectionists
(for localization) were responses to a theory that was simplistic and overweening. The concept of localization that ultimately emerged—and prevailed—is more
subtle by far than anything Gall (or even Wernicke) ever envisioned.
In the aftermath of Wernicke's discovery that there is a modular organization for language in the brain consisting of a complex of serial and parallel processing
centers with more or less independent functions, we now appreciate that all cognitive abilities result from the interaction of many simple processing mechanisms
distributed in many different regions of the brain. Specific brain regions are not concerned with faculties of the mind, but with elementary processing operations.
Perception, movement, language, thought, and memory are all made possible by the serial and parallel interlinking of several brain regions, each with specific
functions. As a result, damage to a single area need not result in the loss of an entire faculty as many earlier neurologists predicted. Even if a behavior initially
disappears, it may partially return as undamaged parts of the brain reorganize their linkages.
Thus, it is not useful to represent mental processes as a series of links in a chain, for in such an arrangement the entire process breaks down when a single link is
disrupted. The better, more realistic metaphor is to think of mental processes as several railroad lines that all feed
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into the same terminal. The malfunction of a single link on one pathway affects the information carried by that pathway, but need not interfere permanently with
the system as a whole. The remaining parts of the system can modify their performance to accommodate extra traffic after the breakdown of a line.
Models of localized function were slow to be accepted because it is enormously difficult to demonstrate which components of a mental operation are represented
by a particular pathway or brain region. Nor has it been easy to analyze mental operations and come up with testable components. Only during the last decade,
with the convergence of modern cognitive psychology and the brain sciences, have we begun to appreciate that all mental functions are divisible into
subfunctions. One difficulty with breaking down mental processes into analytical categories or steps is that our cognitive experience consists of instantaneous,
smooth operations. Actually, these processes are composed of numerous independent information-processing components, and even the simplest task requires
coordination of several distinct brain areas.
To illustrate this point, consider how we learn about, store, and recall the knowledge that we have in our mind about objects, people, and events in our world.
Our common sense tell us that we store each piece of our knowledge of the world as a single representation that can be recalled by memory-jogging stimuli or
even by the imagination alone. Everything we know about our grandmother, for example, seems to be stored in one complete representation of “grandmother”
that is equally accessible to us whether we see her in person, hear her voice, or simply think about her. Our experience, however, is not a faithful guide to the
knowledge we have stored in memory. Knowledge is not stored as complete representations but rather is subdivided into distinct categories and stored
separately. For example, the brain stores separately information about animate and inanimate objects. Thus selected lesions in the left temporal lobe's
association areas can obliterate a patient's knowledge of living things, especially people, while leaving the patient's knowledge of inanimate objects quite intact.
Representational categories such as “living people” can be subdivided even further. A small lesion in the left temporal lobe can destroy a patient's ability to
recognize people by name without affecting the ability to recognize them by sight.
The most astonishing example of the modular nature of representational mental processes is the finding that our very sense of ourselves as a self-conscious
coherent being—the sum of what we mean when we say “I”—is achieved through the connection of independent circuits, each with its own sense of awareness,
that carry out separate operations in our two cerebral hemispheres. The remarkable discovery that even consciousness is not a unitary process was made by
Roger Sperry and Michael Gazzaniga in the course of studying epileptic patients in whom the corpus callosum—the major tract connecting the two
hemispheres—was severed as a treatment for epilepsy. Sperry and Gazzaniga found that each hemisphere had a consciousness that was able to function
independently of the other. The right hemisphere, which cannot speak, also cannot understand language that is well-understood by the isolated left hemisphere.
As a result, opposing commands can be issued by each hemisphere—each hemisphere has a mind of its own! While one patient was holding a favorite book in his
left hand, the right hemisphere, which controls the left hand but cannot read, found that simply looking at the book was boring. The right hemisphere
commanded the left hand to put the book down! Another patient would put on his clothes with the left hand, while taking them off with the other. Thus in some

commissurotomized patients the two hemispheres can even interfere with each other's function. In addition, the dominant hemisphere sometimes comments on
the performance of the nondominant hemisphere, frequently exhibiting a false sense of confidence regarding problems in which it cannot know the solution, since
the information was projected exclusively to the nondominant hemisphere.
Thus the main reason it has taken so long to appreciate which mental activities are localized within which regions of the brain is that we are dealing here with
biology's deepest riddle: the neural representation of consciousness and self-awareness. After all, to study the relationship between a mental process and specific
brain regions, we must be able to identify the components of the mental process that we are attempting to explain. Yet, of all behaviors, higher mental processes
are the most difficult to describe, to measure objectively, and to dissect into their elementary components and operations. In addition, the brain's anatomy is
immensely complex, and the structure and interconnections of its many parts are still not fully understood. To analyze how a specific mental activity is
represented in the brain, we need not only to determine which aspects of the activity are represented in which regions of the brain, but also how they are
represented and how such representations interact.
Only in the last decade has that become possible. By combining the conceptual tools of cognitive psychology with new physiological techniques and brain imaging
methods, we are beginning to visualize the regions of the brain involved in particular behaviors. And we are
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just beginning to discern how these behaviors can be broken down into simpler mental operations and mapped to specific interconnected modules of the brain.
Indeed, the excitement evident in neural science today is based on the conviction that at last we have in hand the proper tools to explore the extraordinary organ
of the mind, so that we can eventually fathom the biological principles that underlie human cognition.

Selected Readings
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Vol. 2, Neuropsychology. pp. 75–95. New York: Plenum.

Caramazza A. 1995. The representation of lexical knowledge in the brain. In: RD Broadwell (ed). Neuroscience, Memory, and Language, Vol. 1, Decade of
the Brain, pp. 133–147. Washington, DC: Library of Congress.

Churchland PS. 1986. Neurophilosophy, Toward a Unified Science of the Mind-Brain. Cambridge, MA: MIT Press.

Cooter R. 1984. The Cultural Meaning of Popular Science: Phrenology and the Organization of Consent in Nineteenth-Century Britain. Cambridge:
Cambridge Univ. Press.

Cowan WM. 1981. Keynote. In: FO Schmitt, FG Worden, G Adelman, SG Dennis (eds). The Organization of the Cerebral Cortex: Proceedings of a
Neurosciences Research Program Colloquium, pp. xi–xxi. Cambridge, MA: MIT Press.

Ferrier D. 1890. The Croonian Lectures on Cerebral Localisation. London: Smith, Elder.

Geschwind N. 1974. Selected Papers on Language and the Brain. Dordrecht, Holland: Reidel.

Harrington A. 1987. Medicine, Mind, and the Double Brain: A Study in Nineteenth-Century Thought. Princeton, NJ: Princeton Univ. Press.

Harrison RG. 1935. On the origin and development of the nervous system studied by the methods of experimental embryology. Proc R Soc Lond B Biol Sci
118:155–196.

Jackson JH. 1884. The Croonian lectures on evolution and dissolution of the nervous system. Br Med J 1:591–593; 660–663; 703–707.

Kandel ER. 1976. The study of behavior: the interface between psychology and biology. In: Cellular Basis of Behavior: An Introduction to Behavioral
Neurobiology, pp. 3–27. San Francisco: Freeman.

Kosslyn SM. 1988. Aspects of a cognitive neuroscience of mental imagery. Science 240:1621–1626.

Marshall JC. 1988. Cognitive neurophysiology: the lifeblood of language. Nature 331:560–561.

Marshall JC. 1988. Cognitive neuropsychology: sensation and semantics. Nature 334:378.

Ojemann GA. 1995. Investigating language during awake neurosurgery. In: RD Broadwell (ed). Neuroscience, Memory, and Language, Vol. 1, Decade of
the Brain, pp. 117–131. Washington, DC: Library of Congress.

Petersen SE. 1995. Functional neuroimaging in brain areas involved in language. In: RD Broadwell (ed). Neuroscience, Memory, and Language, Vol. 1,
Decade of the Brain, pp. 109–116. Washington DC: Library of Congress.

Posner MI, Petersen SE, Fox PT, Raichle ME. 1988. Localization of cognitive operations in the human brain. Science 240:1627–1631.

Ross ED. 1984. Right hemisphere's role in language, affective behavior and emotion. Trends Neurosci 7:342–346.

Shepherd GM. 1991. Foundations of the Neuron Doctrine. New York: Oxford Univ. Press.

Sperry RW. 1968. Mental unity following surgical disconnection of the cerebral hemispheres. Harvey Lect 62:293–323.

Young RM. 1970. Mind, Brain and Adaptation in the Nineteenth Century. Oxford: Clarendon.

References
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Bernard C. 1878–1879. Leçons sur les Phénomènes de la vie Communs aux Animaux et aux Végétaux. Vols. 1, 2. Paris: Baillière.

Boakes R. 1984. From Darwin to Behaviourism: Psychology and the Minds of Animals. Cambridge, England: Cambridge Univ. Press.

Broca P. 1865. Sur le siége de la faculté du langage articulé. Bull Soc Anthropol 6:377–393.

Brodmann K. 1909. Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zeelenbaues. Leipzig: Barth.

Darwin C. 1872. The Expression of the Emotions in Man and Animals. London: Murray.

Descartes R. [1649] 1984. The Philosophical Writings of Descartes. Cambridge: Cambridge Univ. Press.

DuBois-Reymond E. 1848–1849. Untersuchungen über thierische Elektrizität. Vols. 1, 2. Berlin: Reimer.

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Science, Medicine and History, 2:290–302. London: Oxford Univ. Press.

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Galvani L. [1791] 1953. Commentary on the Effect of Electricity on Muscular Motion. RM Green (transl). Cambridge, MA: Licht.

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Back

2
Nerve Cells and Behavior
Eric R. Kandel
HUMANS ARE VASTLY superior to other animals in their ability to exploit their physical environment. The remarkable range of human behavior—indeed, the
complexity of the environment humans have been able to create for themselves—depends on a sophisticated array of sensory receptors connected to a highly
flexible neural machine—a brain—that is able to discriminate an enormous variety of events in the environment. The continuous stream of information from these
receptors is organized by the brain into perceptions (some of which are stored in memory for future reference) and then into appropriate behavioral responses.
All of this is accomplished by the brain using nerve cells and the connections between them.
Individual nerve cells, the basic units of the brain, are relatively simple in their morphology. Although the human brain contains an extraordinary number of these
cells (on the order of 1011 neurons), which can be classified into at least a thousand different types, all nerve cells share the same basic architecture. The
complexity of human behavior depends less on the specialization of individual nerve cells and more on the fact that a great many of these cells form precise
anatomical circuits. One of thekey organizational principles of the brain, therefore, is that nerve cellswith basically similar properties can nevertheless produce
quite differentactions because of the way they are connected with each other and with sensory receptors and muscle.
Since relatively few principles of organization give rise to considerable complexity, it is possible to learn a great deal about how the nervous system produces
behavior by focusing on four basic features of the nervous system:



The mechanisms by which neurons produce signals.


The patterns of connections between nerve cells.


The relationship of different patterns of interconnection to different types of behavior.


The means by which neurons and their connections are modified by experience.

In this chapter we introduce these four features by first considering the structural and functional properties
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of neurons and the glial cells that surround and support them. We then examine how individual cells organize and transmit signals and how signaling between a
few interconnected nerve cells produces a simple behavior, the knee jerk reflex. Finally, we consider how changes in the signaling ability of specific cells can
modify behavior.

The Nervous System Has Two Classes of Cells
There are two main classes of cells in the nervous system: nerve cells (neurons) and glial cells (glia).

Glial Cells Are Support Cells
Glial cells far outnumber neurons—there are between 10 and 50 times more glia than neurons in the central nervous system of vertebrates. The name for these
cells derives from the Greek for glue, although in actuality glia do not commonly hold nerve cells together. Rather, they surround the cell bodies, axons, and
dendrites of neurons. As far as is known, glia are not directly involved in information processing, but they are thought to have at least seven other vital roles:



Glial cells support neurons, providing the brain with structure. They also separate and sometimes insulate neuronal groups and synaptic connections from
each other.


Two types of glial cells (oligodendrocytes and Schwann cells) produce the myelin used to insulate nerve cell axons, the cell outgrowths that conduct
electrical signals.


Some glial cells are scavengers, removing debris after injury or neuronal death.


Glial cells perform important housekeeping chores that promote efficient signaling between neurons (Chapter 14). For example, some glia also take up
chemical transmitters released by neurons during synaptic transmission.


During the brain's development certain classes of glial cells (“radial glia”) guide migrating neurons and direct the outgrowth of axons.


In some cases, as at the nerve-muscle synapse of vertebrates, glial cells actively regulate the properties of the presynaptic terminal.


Some glial cells (astrocytes) help form an impermeable lining in the brain's capillaries and venules— the blood-brain barrier—that prevents toxic
substances in the blood from entering the brain (Appendix B).


Other glial cells apparently release growth factors and otherwise help nourish nerve cells, although this role has been difficult to demonstrate conclusively.

Glial cells in the vertebrate nervous system are divided into two major classes: microglia and macroglia.

Microglia are phagocytes that are mobilized after injury, infection, or disease. They arise from macrophages outside the nervous system and are physiologically
and embryologically unrelated to the other cell types of the nervous system. Not much is known about what microglia do in the resting state, but they become
activated and recruited during infection, injury, and seizure. The activated cell has a process that is stouter and more branched than that of inactivated cells, and
it expresses a range of antigens, which suggests that it may serve as the major antigen presenting cell in the central nervous system. Microglia are thought to
become activated in a number of diseases including multiple sclerosis and AIDS-related dementia, as well as various chronic neurodegenerative diseases such as
Parkinson's disease and Alzheimer's disease.
Three types of macroglial cells predominate in the vertebrate nervous system: oligodendrocytes, Schwann cells, and astrocytes.
Oligodendrocytes and Schwann cells are small cells with relatively few processes. Both types carry out the important job of insulatingaxons, forming a myelin
sheath by tightly winding their membranous processes around the axon in a spiral. Oligodendrocytes, which are found in the central nervous system, envelop an
average of 15 axonal internodes each (Figure 2-1A). By contrast, Schwann cells, which occur in the peripheral nervous system, each envelop just one internode
of only one axon (Figure 2-1B). The types of myelin produced by oligodendrocytes and Schwann cells differ to some degree in chemical makeup.
Astrocytes, the most numerous of glial cells, owe their name to their irregular, roughly star-shaped cell bodies (Figure 2-1C). They tend to have rather long
processes, some of which terminate in end-feet. Some astrocytes form end-feet on the surfaces of nerve cells in the brain and spinal cord and may play a role in
bringing nutrients to these cells. Other astrocytes place end-feet on the brain's blood vessels and cause the vessel's endothelial (lining) cells to form tight
junctions, thus creating the protective blood-brain barrier (Figure 2-1C).
Astrocytes also help to maintain the right potassium ion concentration in the extracellular space between neurons. As we shall learn below and in Chapter 7,
when a nerve cell fires, potassium ions flow out of the cell. Repetitive firing may create an excess of extracellular potassium that could interfere with signaling
between cells in the vicinity. Because astrocytes are highly
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permeable to potassium, they can take up the excess potassium and so protect those neighboring neurons. In addition, astrocytes take up neurotransmitters
from synaptic zones after release and thereby help regulate synaptic activities by removing transmitters. But the role of astrocytes is largely a supporting one.

Figure 2-1 The principal types of glial cells in the central nervous system are astrocytes and oligodendrocytes and in the peripheral nervous
system, Schwann cells.
A. Oligodendrocytes are small cells with relatively few processes. In white matter (left) they provide the myelin, and in gray matter (right) perineural
oligodendrocytes surround and support the cell bodies of neurons. A single oligodendrocyte can wrap its membranous processes around many axons, insulating
them with a myelin sheath.
B. Schwann cells furnish the myelin sheaths that insulate axons in the peripheral nervous system. Each of several Schwann cells, positioned along the length of
a single axon, forms a segment of myelin sheath about 1 mm long. The sheath assumes its form as the inner tongue of the Schwann cell turns around the axon
several times, wrapping it in concentric layers of membrane. The intervals between segments of myelin are known as the nodes of Ranvier. In living cells the
layers of myelin are more compact than what is shown here. (Adapted from Alberts et al. 1994.)
C. Astrocytes, the most numerous of glial cells in the central nervous system, are characterized by their star-like shape and the broad end-feet on their
processes. Because these endfeet put the astrocyte into contact with both capillaries and neurons, astrocytes are thought to have a nutritive function.
Astrocytes also play an important role in forming the bloodbrain barrier.

There is no evidence that glia are directly involved in electrical signaling. Signaling is the function of nerve cells.

Nerve Cells Are the Main Signaling Units of the Nervous System
A typical neuron has four morphologically defined regions: the cell body, dendrites, the axon, and presynaptic terminals (Figure 2-2). As we shall see later, each
of these regions has a distinct role in the generation of signals and the communication of signals between nerve cells.
The cell body (soma) is the metabolic center of the cell. It contains the nucleus, which stores the genes of the cell, as well as the endoplasmic reticulum, an
extension of the nucleus where the cell's proteins are synthesized. The cell body usually gives rise to two kinds of processes: several short dendrites and one,
long, tubular axon. Dendrites branch out in tree-like fashion and are the main apparatus for receiving incoming signals from other nerve cells. In contrast, the
axon extends away from the cell body and is the main conducting unit for carrying signals to other neurons. An axon can convey electrical signals along distances
ranging from 0.1 mm to 3 m. These electrical signals, called action potentials, are rapid, transient, all-or-none nerve impulses, with an amplitude of 100 mV and
a duration of about 1 ms (Figure 2-3). Action potentials are initiated at a specialized trigger region at the origin of the axon called the axon hillock (or initial
segment of the axon); from there they are conducted down the axon without failure or distortion at rates of 1–100 m per second. The amplitude of an action
potential traveling down the axon remains constant because the action potential is an all-or-none impulse that is regenerated at regular intervals along the axon.
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Action potentials constitute the signals by which the brain receives, analyzes, and conveys information. These signals are highly stereotyped throughout the

nervous system, even though they are initiated by a great variety of events in the environment that impinge on our bodies—from light to mechanical contact,
from odorants to pressure waves. Thus, the signals that convey information about vision are identical to those that carry information about odors. Here we
encounter another key principle of brain function. The information conveyed by an action potential is determined not by the form of the signal but by the pathway
the signal travels in the brain. The brain analyzes and interprets patterns of incoming electrical signals and in this way creates our everyday sensations of sight,
touch, taste, smell, and sound.
To increase the speed by which action potentials are conducted, large axons are wrapped in a fatty, insulating sheath of myelin. The sheath is interrupted at
regular intervals by the nodes of Ranvier. It is at these uninsulated spots on the axon that the action potential becomes regenerated. We shall learn more about
myelination in Chapter 4 and about action potentials in Chapter 9.
Near its end, the tubular axon divides into fine branches that form communication sites with other neurons. The point at which two neurons communicate is
known as a synapse. The nerve cell transmitting a signal is called the presynaptic cell. The cell receiving the signal is
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the postsynaptic cell. The presynaptic cell transmits signals from the swollen ends of its axon's branches, called presynaptic terminals. However, a presynaptic
cell does not actually touch or communicate anatomically with the postsynaptic cell since the two cells are separated by a space, the synaptic cleft. Most
presynaptic terminals end on the postsynaptic neuron's dendrites, but the terminals may also end on the cell body or, less often, at the beginning or end of
theaxon of the receiving cell (Figure 2-2).

Figure 2-2 Structure of a neuron. Most neurons in the vertebrate nervous system have several main features in common. The cell body contains the nucleus,
the storehouse of genetic information, and gives rise to two types of cell processes, axons and dendrites. Axons, the transmitting element of neurons, can vary
greatly in length; some can extend more than 3 m within the body. Most axons in the central nervous system are very thin (between 0.2 and 20 µm in
diameter) compared with the diameter of the cell body (50 µm or more). Many axons are insulated by a fatty sheath of myelin that is interrupted at regular
intervals by the nodes of Ranvier. The action potential, the cell's conducting signal, is initiated either at the axon hillock, the initial segment of the axon, or in
some cases slightly farther down the axon at the first node of Ranvier. Branches of the axon of one neuron (the presynaptic neuron) transmit signals to another
neuron (the postsynaptic cell) at a site called the synapse. The branches of a single axon may form synapses with as many as 1000 other neurons. Whereas the
axon is the output element of the neuron, the dendrites (apical and basal) are input elements of the neuron. Together with the cell body, they receive synaptic
contacts from other neurons.

Figure 2-3 This historic tracing is the first published intracellular recording of an action potential. It was obtained in 1939 by Hodgkin and Huxley
from the squid giant axon, using glass capillary electrodes filled with sea water. Time marker is 500 Hz. The vertical scale indicates the potential of the internal
electrode in millivolts, the sea water outside being taken as zero potential. (From Hodgkin and Huxley 1939.)

As we saw in Chapter 1, Ramón y Cajal provided much of the early evidence for the now basic understanding that neurons are the signaling units of the nervous
system and that each neuron is a discrete cell with distinctive processes arising from its cell body (the neuron doctrine). In retrospect, it is hard to appreciate
how difficult it was to persuade scientists of this elementary idea. Unlike other tissues, whose cells have simple shapes and fit into a single field of the light
microscope, nerve cells have complex shapes; the elaborate patterns of dendrites and the seemingly endless course of some axons made it extremely difficult
initially to establish a relationship between these elements. Even after the anatomists Jacob Schleiden and Theodor Schwann put forward the cell theory in the
early 1830s—when the idea that cells are the structural units of all living matter became a central dogma of biology—most anatomists would not accept that the
cell theory applied to the brain, which they thought of as a continuous web-like reticulum.
The coherent structure of the neuron did not become clear until late in the nineteenth century, when Ramón y Cajal began to use the silver staining method
introduced by Golgi. This method, which continues to be used today, has two advantages. First, in a random manner that is still not understood, the silver
solution stains only about 1% of the cells in any particular brain region, making it possible to study a single nerve cell in isolation from its neighbors. Second, the
neurons that do take up the stain are delineated in their entirety, including the cell body, axon, and full dendritic tree. The stain shows that (with rare exceptions
we shall consider later) there is no cytoplasmic continuity between neurons, even at the synapse between two cells. Thus, neurons do not form a syncytium;
each neuron is clearly segregated from every other neuron.
Ramón y Cajal applied Golgi's method to the embryonic nervous systems of many animals, including the human brain. By examining the structure of neurons in
almost every region of the nervous system and tracing the contacts they made with one another, Ramón y Cajal was able to describe the differences between
classes of nerve cells and to map the precise connections between a good many of them. In this way Ramón y Cajal grasped, in addition to the neuron doctrine,
two other principles of neural organization that would prove particularly valuable in studying communication in the nervous system.
The first of these has become known as the principle of dynamic polarization. It states that electrical signals within a nerve cell flow only in one direction: from
the receiving sites of the neuron (usually the dendrites and cell body) to the trigger region at the axon. From there, the action potential is propagated
unidirectionally along the entire length of the axon to the cell's presynaptic terminals. Although neurons vary in shape and function, the operation of most follows
this rule of information flow. Later in this chapter we shall describe the physiological basis of this principle.
The second principle, the principle of connectional specificity, states that nerve cells do not connect indiscriminately with one another to form random networks;
rather each cell makes specific connections—at particular contact points—with certain postsynaptic target cells but not with others. Taken together, the principles
of dynamic polarization and connectional specificity form the cellular basis of the modern connectionist approach to the brain discussed in Chapter 1.
Ramón y Cajal was also among the first to realize that the feature that most distinguishes one neuron from another is shape—specifically, the number and form
of the processes arising from the cell body. On the basis of shape, neurons are classified into three large groups: unipolar, bipolar, and multipolar.

Figure 2-4 Neurons can be classified as unipolar, bipolar, or multipolar according to the number of processes that originate from the cell body.
A. Unipolar cells have a single process, with different segments serving as receptive surfaces or releasing terminals. Unipolar cells are characteristic of the
invertebrate nervous system.
B. Bipolar cells have two processes that are functionally specialized: the dendrite carries information to the cell, and the axon transmits information to other
cells.
C. Certain neurons that carry sensory information, such as information about touch or stretch, to the spinal cord belong to a subclass of bipolar cells designated
as pseudo-unipolar. As such cells develop, the two processes of the embryonic bipolar cell become fused and emerge from the cell body as a single process. This
outgrowth then splits into two processes, both of which function as axons, one going to peripheral skin or muscle, the other going to the central spinal cord.
D. Multipolar cells have an axon and many dendrites. They are the most common type of neuron in the mammalian nervous system. Three examples illustrate
the large diversity of these cells. Spinal motor neurons (left) innervate skeletal muscle fibers. Pyramidal cells (middle) have a roughly triangular cell body;
dendrites emerge from both the apex (the apical dendrite) and the base (the basal dendrites). Pyramidal cells are found in the hippocampus and throughout the
cerebral cortex. Purkinje cells of the cerebellum (right) are characterized by the rich and extensive dendritic tree in one plane. Such a structure permits
enormous synaptic input. (Adapted from Ramón y Cajal 1933.)

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Unipolar neurons are the simplest nerve cells because they have a single primary process, which usually gives rise to many branches. One branch serves as the
axon; other branches function as dendritic receiving structures (Figure 2-4A). These cells predominate in the nervous systems of invertebrates; in vertebrates
they occur in the autonomic nervous system.
Bipolar neurons have an oval-shaped soma that gives rise to two processes: a dendrite that conveys information from the periphery of the body, and an axon
that carries information toward the central nervous system (Figure 2-4B). Many sensory cells are bipolar cells, including those in the retina of the eye and in the
olfactory epithelium of the nose. The mechanoreceptors that convey touch, pressure, and pain to the spinal cord are variants of bipolar cells called pseudounipolar cells. These cells develop initially as bipolar cells; later the two cell processes fuse to form one axon that emerges from the cell body. The axon then
splits into two; one branch runs to the periphery (to sensory receptors in the skin, joints, and muscle), the other to the spinal cord (Figure 2-4C).
Multipolar neurons predominate in the nervous system of vertebrates. They have a single axon and, typically, many dendrites emerging from various points
around the cell body (Figure 2-4D). Multipolar cells vary greatly in shape, especially in the length of their
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axons and in the number, length, and intricacy of dendrite branching. Usually the number and extent of their dendrites correlate with the number of synaptic
contacts that other neurons make onto them. A spinal motor cell with a relatively modest number of dendrites receives about 10,000 contacts—2000 on its cell
body and 8000 on its dendrites. The dendritic tree of a Purkinje cell in the cerebellum is much larger and bushier, as well it might be—it receives approximately
150,000 contacts!
Neurons are also commonly classified into three major functional groups: sensory, motor, and interneuronal. Sensory neurons carry information from the body's
periphery into the nervous system for the purpose of both perception and motor coordination.1 Motor neurons carry commands from the brain or spinal cord to
muscles and glands. Interneurons constitute by far the largest class, consisting of all nerve cells that are not specifically sensory or motor. Interneurons are
subdivided into two classes. Relay or projection interneurons have long axons and convey signals over considerable distances, from one brain region to another.
Local interneurons have short axons and process information within local circuits.

Nerve Cells Form Specific Signaling Networks That Mediate Specific Behaviors
All the behavioral functions of the brain—the processing of sensory information, the programming of motor and emotional responses, the vital business of storing
information (memory)—are carried out by specific sets of interconnected neurons. Here we shall examine in general terms how a behavior is produced by
considering a simple stretch reflex, the knee jerk. We shall see how a transient imbalance of the body, which puts a stretch on the extensor muscles of the leg,
produces sensory information that is conveyed to motor cells, which in turn convey commands to the extensor muscles to contract so that balance will be
restored.
The anatomical components of the knee jerk are shown in Figure 2-5. The tendon of the quadriceps femoris, an extensor muscle that moves the lower leg, is
attached to the tibia through the tendon of the kneecap, the patellar tendon. Tapping this tendon just below the patella will pull (stretch) the quadriceps femoris.
This initiates a reflex contraction of the quadriceps muscle to produce the familiar knee jerk, an extension of the leg smoothly coordinated with a relaxation of the
hamstrings, the opposing flexor muscles. By increasing the tension of a selected group of muscles, the stretch reflex changes the position of the leg, suddenly
extending it outward. (The regulation of movement by the nervous system is discussed in Section VI.)

Figure 2-5 The knee jerk is an example of a monosynaptic reflex system, a simple behavior controlled by directconnections between sensory
and motor neurons. Tapping the kneecap with a reflex hammer pulls on the tendon of the quadriceps femoris, an extensor muscle that extends the lower leg.
When the muscle stretches in response to the pull of the tendon, information regarding this change in the muscle is conveyed by afferent (sensory) neurons to
the central nervous system. In the spinal cord the sensory neurons act directly on extensor motor neurons that contract the quadriceps, the muscle that was
stretched. In addition, the sensory neurons act indirectly, through interneurons, to inhibit flexor motor neurons that would otherwise contract the opposing
muscle, the hamstring. These actions combine to produce the reflex behavior. In this schematic drawing each extensor and flexor motor neuron represents a
population of many cells.

Stretch reflexes like the knee jerk are a special type of reflex called spinal reflexes, behaviors mediated by neural circuits that are entirely confined to the spinal
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cord. As we shall see later in the book, such spinal circuits relieve the major motor systems of the brain of having to micromanage elementary behavioral actions.
Stretch reflexes are mediated in good part by monosynaptic circuits, in which the sensory neurons and motor neurons executing the action are directly connected
to one another, with no interneuron intervening between them. Most other reflexes, including most spinal reflexes, use polysynaptic circuits that include one or
more sets of interneurons. Polysynaptic circuits are more amenable to modification by the brain's higher processing centers.
The cell bodies of the mechanoreceptor sensory neurons involved in the knee jerk are clustered near the spinal cord in a dorsal root ganglion (Figure 2-5). They
are pseudo-unipolar cells; one branch of the cell's axongoes to the quadriceps muscle at the periphery, while the other runs centrally into the spinal cord. The
branch that innervates the quadriceps makes contact with stretchsensitive receptors called muscle spindles and is excited when the muscle is stretched. The
branch in the spinal cord forms excitatory connections with the motor neurons that innervate the quadriceps and control its contraction. In addition, this branch
contacts local interneurons that inhibit the motor neurons controlling the opposing flexor muscles. These local interneurons are not involved in the stretch reflex
itself, but by coordinating motor action they increase the stability of the reflex response. Thus, the electrical signals that produce the stretch reflex convey four
kinds of information:



Sensory information is conveyed to the central nervous system (the spinal cord) from the body's surface.


Motor commands from the central nervous system are issued to the muscles that carry out the knee jerk.


Complementary, inhibitory commands are issued to motor neurons that innervate opposing muscles, providing coordination of muscle action.


Information about local neuron activity related to the knee jerk is conveyed to higher centers of the central nervous system, thus permitting the brain to
coordinate behavioral commands.

The stretching of just one muscle, the quadriceps, activates several hundred sensory neurons, each of which makes direct contact with 100–150 motor neurons
(Figure 2-6A). This pattern of connection, in which one neuron activates many target cells, is called neuronal divergence; it is especially common in the input
stages of the nervous system. By distributing its signals to many target cells, a single neuron can exert wide and diverse influence. For example, sensory neurons
involved in a stretch reflex also contact projection interneurons that transmit information about the local neural activity to higher brain regions concerned with
coordinating movements. In contrast, because there are usually five to 10 times more sensory neurons than motor neurons, a single motor cell typically receives
input from many sensory cells (Figure 2-6B). This pattern of connection, called convergence, is common at the output stages of the nervous system. By receiving
signals from numerous neurons, the target motor cell is able to integrate diverse information from many sources.

Figure 2-6 Diverging and convergingneuronal connections are a key organizational feature of the brain.
A. In the sensory systems receptor neurons at the input stage usually branch out and make multiple, divergent connections with neurons that represent the
second stage of processing. Subsequent connections diverge even more.
B. By contrast, motor neurons are the targets of progressively converging connections. With convergence, the target cell receives the sum of information from
many presynaptic cells.

A stretch reflex such as the knee jerk is a simple behavior produced by two classes of neurons connecting at excitatory synapses. But not all important signals in
the brain are excitatory. In fact, half of all neurons produce inhibitory signals. Inhibitory neurons release a transmitter that reduces the likelihood of firing. As we
have seen, even in the knee-jerk reflex, the sensory neurons make both excitatory connections and connections through inhibitory interneurons. Excitatory
connections with the leg's extensor muscles cause these muscles to contract, while connections with certain inhibitory interneurons prevent the antagonist flexor
muscles from being called to action. This feature of the circuit is an example of feed-forward inhibition (Figure 2-7A). Feedforward inhibition in the knee-jerk
reflex is reciprocal, ensuring that the flexor and extensor pathways always
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inhibit each other, so only muscles appropriate for the movement, and not those that oppose it, are recruited.

Figure 2-7 Inhibitory interneurons can produce either feed forward or feedback inhibition.
A. Feed-forward inhibition is common in monosynaptic reflex systems, such as the knee-jerk reflex (see Figure 2-5). Afferent neurons from extensor muscles
excite not only the extensor motor neurons, but also inhibitory neurons that prevent the firing of the motor cells in the opposingflexor muscles. Feedforward
inhibition enhances the effect of the active pathway by suppressing the activity of other, opposing, pathways.
B. Negative feedback inhibition is a self-regulating mechanism. The effect is to dampen activity within the stimulated pathway and prevent it from exceeding a
certain critical maximum. Here the extensor motor neurons act on inhibitory interneurons, which feed back to the extensor motor neurons themselves and thus
reduce the probability of firing by these cells.

Neurons can also have connections that provide feedback inhibition. For example, an active neuron may have excitatory connections withboth a target cell and an
inhibitory interneuron that has its own feedbackconnection with the active neuron. In this way signals from the active neuron simultaneously excite the target
neuron and the inhibitory interneuron, which thus is able to limit the ability of the active neuron to excite its target (Figure 2-7B). We will encounter many
examples of feed-forward and feedback inhibition when we examine more complex behaviors in later chapters.

Signaling Is Organized in the Same Way in All Nerve Cells
To produce a behavior, a stretch reflex for example, each participating sensory and motor nerve cell sequentially generates four different signals at different sites
within the cell: an input signal, a trigger signal, a conducting signal, and an output signal. Regardless of cell size and shape, transmitter biochemistry, or
behavioral function, almost all neurons can be described by a model neuron that has four functional components, or regions, that generate the four types of
signals (Figure 2-8): a local input (receptive) component, a trigger (summing or integrative) component, a long-range conducting (signaling) component, and an
output (secretory) component. This model neuron is the physiological representation of Ramón y Cajal's principle of dynamic polarization.
The different types of signals used by a neuron are determined in part by the electrical properties of the cell membrane. At rest, all cells, including neurons,
maintain a difference in the electrical potential on either side of the plasma (external) membrane. This is called the resting membrane potential. In a typical
resting neuron the electrical potential difference is about 65 mV. Because the net charge outside of the membrane is arbitrarily defined as zero, we say the
resting membrane potential is -65 mV. (In different nerve cells it may range from about -40 to -80 mV; in muscle cells it is greater still, about -90 mV.) As we
shall see in Chapter 7, the difference in electrical potential when the cell is at rest results from two factors: (1) the unequal distribution of electrically charged
ions, in particular, the positively charged Na+ and K+ ions and the negatively charged amino acids and proteins on either side of the cell membrane, and (2) the
selective permeability of the membrane to just one of these ions, K+.
The unequal distribution of positively charged ions on either side of the cell membrane is maintained by a membrane protein that pumps Na+ out of the cell and K
+

back into it. This Na+-K+ pump, which we shall learn more about in Chapter 7, keeps the Na+ ion concentration in the cell low (about 10 times lower than that

outside the cell) and the K+ ion concentration high (about 20 times higher than that outside).
At the same time, the cell membrane is selectively permeable to K+ because the otherwise impermeable membrane contains ion channels, pore-like structures
that span the membrane and are highly permeable to K+ but considerably less permeable to Na+. When the cell is at rest, these channels are open and K+ ions
tend to leak out. As K+ ions leak from the cell, they leave behind a cloud of unneutralized negativecharge on the inner surface of the membrane, so that the net
charge inside
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the membrane is more negative than on the outside (Figure 2-9).

Figure 2-8 Most neurons, regardlessof type, have four functional regions in common: an input component, a trigger or integrative component, a
conductile component, and an output component. Thus, the functional organization of most neurons can be schematically represented by a model neuron.
Each component produces a characteristic signal: the input, integrative, and conductile signals are all electrical, while the output signal consists of the release of
a chemical transmitter into the synaptic cleft. Not all neurons share all these features; for example, local interneurons often lack a conductile component.

Excitable cells, such as nerve and muscle cells, differ from other cells in that their membrane potential can be significantly and quickly altered; this change can
serve as a signaling mechanism. Reducing the membrane potential by say 10 mV (from -65 mV to -55 mV) makes the membrane much more permeable to Na+
than to K+. This influx of positively charged Na+ ions tends to neutralize the negative charge inside the cell and results in an even greater reduction in membrane
potential— the action potential. The action potential is conducted down the cell's axon to the axon's terminals which end on other cells (neurons or muscle),
where the action potential initiates communication with the other cells. As noted earlier, the action potential is an all-or-none impulse that is actively propagated
along the axon, so that its amplitude is not diminished by the time it reaches the axon terminal. Typically, an action potential lasts about one millisecond, after
which the membrane returns to its resting state, with its normal separation of charges and higher permeability to K+ than to Na+. We shall learn more about the
mechanisms underlying the resting potential and action potential in Chapters 6,7,8,9.

In addition to the long-range signal of the action potential, nerve cells also produce local signals, such as receptor potentials and synaptic potentials, that are not
actively propagated and therefore typically decay within just a few millimeters. Both long-range and local signals result from changes in the membrane potential,
either a decrease or increase from the resting potential. The resting membrane potential therefore provides the baseline against which all signals are expressed.
A reduction in membrane potential (eg, from -65 mV to -55 mV) is called depolarization. Because depolarization enhances a cell's ability to generate an action
potential, it is excitatory. In contrast, an increase in membrane potential (eg, from about -65 mV to -75 mV) is called hyperpolarization. Hyperpolarization makes
a cell less likely to generate an action potential and is therefore inhibitory.

The Input Component Produces Graded Local Signals
In most neurons at rest no current flows from one part of the neuron to another, so the resting potential is the same throughout the cell. In sensory neurons
current flow is typically initiated by a sensory stimulus, which activates specialized receptor proteins at the neuron's receptive surface. In our example of the
knee jerk,
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stretch of the quadriceps muscle activates specific proteins that are sensitive to stretch of the sensory neuron. The specialized receptor protein forms ion
channels in the membrane, through which Na+ and K+ flow. These channels open when the cell is stretched, as we shall learn in Chapters 7 and 9, permitting a
rapid influx of ions into the sensory cell. This ionic current disturbs the resting potential of the cell membrane, driving the membrane potential to a new level
called the receptor potential. The amplitude and duration of the receptor potential depends on the intensity of the muscle stretch. The larger or longer-lasting the
stretch, the larger and longer-lasting the resulting receptor potential (Figure 2-10A). Most receptor potentials are depolarizing (excitatory). However,
hyperpolarizing (inhibitory) receptor potentials are found in the retina of the eye, as we shall learn in Chapter 26.

Figure 2-9 The membrane potential of a cell results from a difference in the net electrical charge on either side of its membrane. When a neuron
is at rest there is an excess of positive charge outside the cell and an excess of negative charge inside it.

The receptor potential is the first representation of stretch to be coded in the nervous system. It is, however, a purely local signal. The receptor potential—the
electrical activity in the sensory neuron initiated by a stimulus —spreads only passively along the axon. It therefore decreases in amplitude with distance and
cannot be conveyed much farther than 1 or 2 mm. In fact, at about 1 mm down the axon the amplitude of the signal is only about one-third what it was at the
site of generation. To be carried successfully to the rest of the nervous system, the local signal must be amplified—it must generate an action potential. In the
knee jerk the receptor potential in the sensory neuron propagates to the first node of Ranvier in the axon, where, if it is large enough, it generates an action
potential, which then propagates without failure (by a regenerative mechanism discussed in Chapter 9) to the axon terminals in the spinal cord. Here, at the
synapse, between the sensory neuron and a motor neuron activating the leg muscles, the action potential produces a chain of events that result in an input signal
to the motor neuron.
In our example of the knee jerk, the action potential in the sensory neuron releases a chemical signal (a neurotransmitter) across the synaptic cleft. The
transmitter binds to receptor proteins on the motor neuron, and the resulting reaction transduces the potential chemical energy of the transmitter into electrical
energy. This in turn alters the membrane potential of the motor cell, a change called the synaptic potential.
Like the receptor potential, the synaptic potential is graded. The amplitude of the synaptic potential depends on how much chemical transmitter is released, and
its duration on how long the transmitter is active. The synaptic potential can be either depolarizing or hyperpolarizing, depending on the type of receptor
molecule that is activated. Synaptic potentials, like receptor potentials, are local changes in membrane potential that spread passively along the neuron. The
signal does not reach beyond the axon's initial segment unless it gives rise to an action potential. The features ofreceptor and synaptic potentials are summarized
in Table 2-1.

The Trigger Component Makes the Decision to Generate an Action Potential
Charles Sherrington first pointed out that the quintessential action of the nervous system is its ability to weigh the consequences of different types of information
and then decide on appropriate responses. This integrative action of the nervous system is clearly seen in the actions of the trigger component of the neuron.
Action potentials are generated by a sudden influx of Na+ ions through voltage-sensitive channels in the cell membrane. When an input signal (a receptor
potential or synaptic potential) depolarizes the cell membrane, the change in membrane potential opens the Na+ ion channels, allowing Na+ to flow down its
concentration gradient, from outside the cell where the Na+ con-

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centration is high to inside the cell where it is low. These voltage-sensitive Na+ channels are concentrated at the initial segment of the axon, an uninsulated
portion of the axon just beyond the neuron's input region. In sensory neurons the highest density of Na+ channels occurs at the myelinated axon's first node of
Ranvier; in interneurons and motor neurons the highest density occurs at the axon hillock, where the axon emerges from the cell body.

Figure 2-10 A sensory neuron transforms a physical stimulus (in our example, a stretch) into electrical activity in the cell. Each of the neuron's
four signaling components produces a characteristic signal.
A. The input signal (a receptor or synaptic potential) is graded in amplitude and duration, proportional to the amplitude and duration of the stimulus.
B. The trigger zone integrates the input signal—the receptor potential in sensory neurons, or synaptic potential in motor neurons—into a trigger action that
produces action potentials that will be propagated along the axon. An action potential is generated only if the input signal is greater than a certain spike
threshold. Once the input signal surpasses this threshold, any further increase in amplitude of the input signal increases the frequency with which the action
potentials are generated, not their amplitude. The duration of the input signal determines the number of action potentials. Thus, the graded nature of input
signals is translated into a frequency code of action potentials at the trigger zone.
C. Action potentials are all-or-none. Every action potential has the same amplitude and duration, and thus the same wave form on an oscilloscope. Since action
potentials are conducted without fail along the full length of the axon to the synaptic terminals, the information in the signal is represented only by the
frequency and number of spikes, not by the amplitude.
D. When the action potential reaches the synaptic terminal, the cell releases a chemical neurotransmitter that serves as the output signal. The total number of
action potentials in a given period of time determines exactly how much neurotransmitter will be released by the cell.

Because it has the highest density of voltagesensitive Na+ channels, the initial segment of the axon has the lowest threshold for generating an action potential.
Thus, an input signal spreading passively along the cell membrane is more likely to give rise to an action potential at the initial segment of the axon than at other
sites in the cell. This part of the axon is therefore known as the impulse initiation zone, or trigger zone. It is here that the activity of all receptor (or synaptic)
potentials is summed and where, if the size of the input signal reaches threshold, the neuron fires an action potential.
Table 2-1 Comparison of Local (Passive) and Propagated Signals
Signal type

Amplitude (mV)

Duration

Summation

Effect of signal

Type of propagation

Local (passive) signals
Receptor potentials

Small (0.1–10)

Brief (5–100 ms)

Graded

Hyperpolarizing or depolarizing

Passive

Synaptic potentials

Small (0.1–10)

Brief to long (5 ms to 20 min)

Graded

Hyperpolarizing or depolarizing

Passive

Brief (1–10 ms)

All-or-none

Depolarizing

Active

Propagated (active) signals
Action potentials

Large (70–110)

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The Conductile Component Propagates an All-or-None Action Potential
The action potential, the conducting signal of the neuron, is all-or-none. This means that while stimuli below the threshold will not produce a signal, all stimuli

above the threshold produce the same signal. However much the stimuli vary in intensity or duration, the amplitude and duration of each action potential are
pretty much the same. In addition, unlike receptor and synaptic potentials, which spread passively and decrease in amplitude, the action potential does not decay
as it travels along the axon to its target—a distance that can measure 3 m in length—because it is periodically regenerated. This conducting signal can travel at
rates as fast as 100 meters per second.
The remarkable feature of action potentials is that they are highly stereotyped, varying only subtly (although in some cases importantly) from one nerve cell to
another. This feature was demonstrated in the 1920s by Edgar Adrian, who was one of the first to study the nervous system at the cellular level. Adrian found
that all action potentials have a similar shape or wave form on the oscilloscope (see Figure 2-3). Indeed, the voltage signals of action potentials carried into the
nervous system by a sensory axon often are indistinguishable from those carried out of the nervous system to the muscles by a motor axon.
Only two features of the conducting signal convey information: the number of action potentials and the time intervals between them (Figure 2-10C). As Adrian
put it in 1928, summarizing his work on sensory fibers: “… all impulses are very much alike, whether the message is destined to arouse the sensation of light, of
touch, or of pain; if they are crowded together the sensation is intense, if they are separated by long intervals the sensation is correspondingly feeble.” Thus,
what determines the intensity of sensation or speed of movement is not the magnitude or duration of individual action potentials, but their frequency. Likewise,
the duration of a sensation or movement is determined by the period over which action potentials are generated.
If signals are stereotyped and do not reflect the properties of the stimulus, how do neural signals carry specific behavioral information? How is a message that
carries visual information distinguished from one that carries pain information about a bee sting, and how do both of these signals differ from messages that send
commands for voluntary movement? As we have seen, and will learn to appreciate even more in later chapters, the message of an action potential is determined
by the neural pathway that carries it. The visual pathways activated by receptor cells in the retina that respond to light are completely distinct from the somatic
sensory pathways activated by sensory cells in the skin that respond to touch or to pain. The function of the signal—be it visual, tactile, or motor—is determined
not by the signal itself but by the pathway along which it travels.

The Output Component Releases Neurotransmitter
When an action potential reaches a neuron's terminal it stimulates the release of a chemical transmitter from the cell. Transmitters can be small molecules, such
as L-glutamate and acetylcholine, or they can be peptides like enkephalin (Chapter 15). Transmitter molecules are held in subcellular organelles called synaptic
vesicles, which are loaded into specialized release sites in the presynaptic terminals called active zones. To unload their transmitter, the vesicles move up to and
fuse with the neuron's plasma membrane, a process known as exocytosis. (We shall consider neurotransmitter release in Chapter 14.)
The release of chemical transmitter serves as a neuron's output signal. Like the input signal, the output signal is graded. The amount of transmitter released is
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determined by the number and frequency of the action potentials in the presynaptic terminals (see Figure 2-10). After the transmitter is released from the
presynaptic neuron, it diffuses across the synaptic cleft to receptors in the membrane of the postsynaptic neuron. The binding of transmitter to receptors causes
the postsynaptic cell to generate a synaptic potential. Whether the synaptic potential has an excitatory or inhibitory effect will depend on the type of receptors in
the postsynaptic cell, not on the particular neurotransmitter. The same transmitter can have different effects on different types of receptors.

Figure 2-11 The sequence of signals that produces a reflex action.
1. The stretching of a muscle produces a receptor potential in the terminal fibers of the sensory neuron (the dorsal root ganglion cell). The amplitude of the
receptor potential is proportional to the intensity of the stretch. This potential then spreads passively to the integrative segment, or trigger zone, at the first
node of Ranvier. There, if the receptor potential is sufficiently large, it triggers an action potential, which then propagates actively and without change along the
axon to the terminal region. At the terminal the action potential leads to an output signal: the release of a chemical neurotransmitter. The transmitter diffuses
across the synaptic cleft and interacts with receptor molecules on the external membranes of the motor neurons that innervate the stretched muscle. 2. This
interaction initiates a synaptic potential in the motor cell. The synaptic potential then spreads passively to the trigger zone of the motor neuron axon, where it
initiates an action potential that propagates actively to the terminal of the motor neuron. The action potential releases transmitter at the nerve-muscle synapse.
3. The binding of the neurotransmitter with receptors in the muscle triggers a synaptic potential in the muscle. This signal produces an action potential in the
muscle, causing con-traction of the muscle fiber.

The Transformation of the Neural Signal From Sensory to Motor Is Illustrated by the Stretch
Reflex Pathway
We have seen that a signal is transformed as it is conveyed from one component of the neuron to the next and from one neuron to the next. This
transformation— from input to output—can be seen in perspective by tracing the relay of signals for the stretch reflex.
When a muscle is stretched, the features of the stimulus —its amplitude and duration—are reflected in the amplitude and duration of the receptor potential in the
sensory neuron. If the receptor potential exceeds the threshold for action potentials in that cell, the graded signal is transformed at the trigger component into an
action potential, an all-or-none signal. The more the receptor potential exceeds threshold, the greater the depolarization and consequently the greater the
frequency of action potentials in the axon; likewise, the duration of the input signal determines the number of action potentials. (Several action potentials
together are called a train of action potentials.) This information—the frequency and number of action potentials—is then faithfully conveyed along the entire
axon's length to its terminals, where the frequency of action potentials determines how much transmitter is released.
These stages of transformation have their counterparts in the motor neuron. The transmitter released by a sensory neuron interacts with receptors on the motor
neuron to initiate a graded synaptic potential, which spreads to the initial segment of the motor axon. If the membrane potential of the motor neuron reaches a

critical threshold, an action potential will be generated and propagate without fail to the motor cell's presynaptic terminals. There the action potential causes
transmitter release, which triggers a synaptic potential in the muscle. That in turn produces an action potential in the leg muscle, which leads to the final
transformation —muscle contraction and an overt behavior. The sequence of transformations of a signal from senP.33
sory neuron to motor neuron to muscle is illustrated in Figure 2-11.

Nerve Cells Differ Most at the Molecular Level
The model of neuronal signaling we have outlined is a simplification that applies to most neurons, but there are some important variations. For example, some
neurons do not generate action potentials. These are typically local interneurons without a conductile component—they have no axon, or such a short one that a
conducted signal is not required. In these neurons the input signals are summed and spread passively to the nearby terminal region, where transmitter is
released. There are also neurons that lack a steady resting potential and are spontaneously active.
Even cells with similar organization can differ in important molecular details, expressing different combinations of ion channels, for example. As we shall learn in
Chapters 6 and 9, different ion channels provide neurons with various thresholds, excitability properties, and firing patterns. Thus, neurons with different ion
channels can encode the same class of synaptic potential into different firing patterns and thereby convey different signals.
Neurons also differ in the chemical transmitters they use to transmit information to other neurons, and in the receptors they have to receive information from
other neurons. Indeed, many drugs that act on the brain do so by modifying the actions of specific chemical transmitters or a particular subtype of receptor for a
given transmitter. These differences not only have physiological importance for day-to-day functioning of the brain, but account for the fact that a disease may
affect one class of neurons but not others. Certain diseases, such as amyotrophic lateral sclerosis and poliomyelitis, strike only motor neurons, while others, such
as tabes dorsalis, a late stage of syphilis, affect primarily sensory neurons. Parkinson's disease, a disorder of voluntary movement, damages a small population of
interneurons that use dopamine as a chemical transmitter. Some diseases are selective even within the neuron, affecting only the receptive elements, the cell
body, or the axon. In Chapter 16 we shall see how research into myasthenia gravis, caused by a faulty transmitter receptor in the muscle membrane, has
provided important insights into synaptic transmission. Indeed, because the nervous system has so many cell types and variations at the molecular level, it is
susceptible to more diseases (psychiatric as well as neurological) than any other organ of the body.
Despite the differences among nerve cells, the basic mechanisms of electrical signaling are surprisingly similar. This simplicity is fortunate for those who study
the brain. By understanding the molecular mechanisms that produce signaling in one kind of nerve cell, we are well on the way to understanding these
mechanisms in many other nerve cells.

Nerve Cells Are Able to Convey Unique Information Because They Form Specific Networks
The stretch reflex illustrates how just a few types of nerve cells can interact to produce a simple behavior. But even the stretch reflex involves populations of
neurons— perhaps a few hundred sensory neurons and a hundred motor neurons. Can the individual neurons implicated in a complex behavior be identified with
the same precision? In invertebrate animals, and in some lower vertebrates, a single cell (the so-called command cell) can initiate a complex behavioral
sequence. But, as far as we know, no complex human behavior is initiated by a single neuron. Rather, each behavior is generated by the actions of many cells.
Broadly speaking, as we have seen, there are three neural components of behavior: sensory input, intermediate (interneuronal) processing, and motor output.
Each of these components is mediated by a single group or several distinct groups of neurons.
As discussed in Chapter 1, one of the key strategies of the nervous system is localization of function: specific types of information are processed in particular
brain regions. Thus, information for each of our senses is processed in a distinct brain region where the afferent connections typically form a precise map of the
pertinent receptor sheet on the body surface—the skin (touch), the retina (sight), the basilar membrane of the cochlea (hearing), or the olfactory epithelium
(smell). These maps are the first stage in creating a representation in the brain of the outside world in which we live. Similarly, areas of the brain concerned with
movement contain an orderly arrangement of neural connections representing the musculature and specific movements. The brain, therefore, contains at least
two types of neural maps: one for sensory perceptions and another for motor commands. The two maps are interconnected in ways we do not yet fully
understand.
The neurons that make up these maps—motor, sensory, and interneuronal—do not differ greatly in their electrical properties. They have different functions
because of the connections they make. These connections, established as the brain develops, determine the behavioral function of individual cells. Although our
understanding of how sensory and motor information is processed and represented in the brain is based on the
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detailed studies of only a few regions, in those regions in which our understanding is particularly well advanced it is clear that the logical operations of a mental
representation can be understood only by defining the flow of information through the connections that make up the various maps.
A single component of behavior sometimes recruits a number of groups of neurons that simultaneously provide the same or similar information. The deployment
of several neuron groups or several pathways to convey similar information is called parallel processing. Parallel processing also occurs in a single pathway when
different neurons in the pathway perform similar computations simultaneously. Parallel processing makes enormous sense as an evolutionary strategy for
building a more powerful brain: it increases both the speed and reliability of function within the central nervous system.
The importance of abundant, highly specific parallel connections is now also being recognized by scientists attempting to construct computer models of the brain.
Scientists working in this field, a branch of computer science known as artificial intelligence, first used serial processing to simulate the brain's higher-level
cognitive processes—processes such as pattern recognition, learning, memory, and motor performance. They soon realized that although these serial models
solved many problems rather well, including the challenge of playing chess, they performed poorly with other computations that the brain does almost
instantaneously, such as recognizing faces or comprehending speech.
As a result, most computational neurobiologists have turned to systems with both serial and parallel (distributed) components, which they call connectionist
models. In these models elements distributed throughout the system process related information simultaneously. Preliminary insights from this work are often
consistent with physiological studies. Connectionist models show that individual elements of a system do not transmit large amounts of information. Thus, what
makes the brain a remarkable information processing machine is not the complexity of its neurons, but rather its many elements and, in particular, the
complexity of connections between them. Individual stereotyped neurons are able to convey unique information because they are wired together and organized in
different ways.

The Modifiability of Specific Connections Contributes to the Adaptability of Behavior
That neurons make specific connections with one another simple reflexes can undergo modification that lasts minutes, and much learning results in behavioral
change that can endure for years. How can neural activity produce such long-term changes in the function of a set of prewired connections? A number of
solutions for these dilemmas have been proposed. The proposal that has proven most farsighted is the plasticity hypothesis, first put forward at the turn of the
century by Ramón y Cajal. A modern form of this hypothesis was advanced by the Polish psychologist Jerzy Konorski in 1948:
The application of a stimulus leads to changes of a twofold kind in the nervous system. … [T]he first property, by virtue of which the nerve cells react to the
incoming impulse … we call excitability, and … changes arising … because of this property we shall call changes due to excitability. The second property, by virtue
of which certain permanent functional transformations arise in particular systems of neurons as a result of appropriate stimuli or their combination, we shall call
plasticity and the corresponding changes plastic changes.

There is now considerable evidence for plasticity at chemical synapses. Chemical synapses often have a remarkable capacity for short-term physiological changes
(lasting hours) that increase or decrease the effectiveness of the synapse. Long-term changes (lasting days) can give rise to further physiological changes that
lead to anatomical changes, including pruning of preexisting connections, and even growth of new connections. As we shall see in later chapters, chemical
synapses can be modified functionally and anatomically during development and regeneration, and, most importantly, through experience and learning.
Functional alterations are typically short term and involve changes in the effectiveness of existing synaptic connections. Anatomical alterations are typically longterm and consist of the growth of new synaptic connections between neurons. It is this potential for plasticity of the relatively stereotyped units of the nervous
system that endows each of us with our individuality.

Selected Readings
Adrian ED. 1928. The Basis of Sensation: The Action of the Sense Organs. London: Christophers.

Gazzaniga MS (ed). 1995. The Cognitive Neurosciences. Cambridge, MA: MIT Press.
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Jones EG. 1988. The nervous tissue. In: LWeiss (ed), Cell and Tissue Biology: A Textbook of Histology, 6th ed., pp. 277–351. Baltimore: Urban and
Schwarzenberg.

Newan EA. 1993. Inward-rectifying potassium channels in retinal glial (Muller) cells. J Neurosci 13:3333–3345.

Perry VH. 1996. Microglia in the developing and mature central nervous system. In: KR Jessen, WD Richardson (eds).Glial Cell Development: Basic
Principles & Clinical Relevance, pp. 123–140. Oxford: Bios.

Ramón y Cajal S. 1937. 1852–1937. Recollections of My Life. EH Craigie (transl). Philadelphia: American Philosophical Society; 1989. Reprint. Cambridge,
MA: MIT Press.

References
Adrian ED. 1932. The Mechanism of Nervous Action: Electrical Studies of the Neurone. Philadelphia: Univ. Pennsylvania Press.

Alberts B, Bray D, Lewis J, Raff M, Roberts K, Watson JD. 1994. Molecular Biology of the Cell, 3rd ed. New York: Garland.

Erlanger J, Gasser HS. 1937. Electrical Signs of Nervous Activity. Philadelphia: Univ. Pennsylvania Press.

Hodgkin AL, Huxley AF. 1939. Action potentials recorded from inside a nerve fiber. Nature 144:710–711.

Kandel ER. 1976. The study of behavior: the interface between psychology and biology. In: Cellular Basis of Behavior: An Introduction to Behavioral
Neurobiology, pp. 3–27. San Francisco: WH Freeman.

Konorski J. 1948. Conditioned Reflexes and Neuron Organization. Cambridge: Cambridge Univ. Press.

Martinez Martinez PFA. 1982. Neuroanatomy: Development and Structure of the Central Nervous System. Philadelphia: Saunders.

Newman EA. 1986. High potassium conductance in astrocyte endfeet. Science 233:453–454.

Nicholls JG, Martin AR, Wallace BG. 1992. From Neuron to Brain: A Cellular and Molecular Approach to the Function of the Nervous System, 3rd ed.
Sunderland, MA: Sinauer.

Penfield W (ed). 1932. Cytology & Cellular Pathology of the Nervous System, Vol. 2. New York: Hoeber.

Ramón y Cajal S. 1933. Histology, 10th ed. Baltimore: Wood.

Sears ES, Franklin GM. 1980. Diseases of the cranial nerves. In: RN Rosenberg (ed). The Science and Practice of Clinical Medicine. Vol. 5, Neurology, pp.
471–494. New York: Grune & Stratton.

Sherrington C. 1947. The Integrative Action of the Nervous System, 2nd ed. Cambridge: Cambridge Univ. Press
1.

Some primary sensory neurons are also commonly called afferent neurons, and we use these two terms interchangeably in the book. The term afferent (carried
toward the nervous system) applies to all information reaching the central nervous system from the periphery, whether or not this information leads to sensation.
The term sensory should, strictly speaking, be applied only to afferent input that leads to a perception.

Back

3
Genes and Behavior
T. Conrad Gilliam
Eric R. Kandel
Thomas M. Jessell
ALL BEHAVIOR IS SHAPED BY the interplay of genes and the environment. Even the most stereotypic behaviors of simple animals can be influenced by the
environment, while highly evolved behaviors in humans, such as language, are constrained by hereditary factors. In this chapter we review what is known about
the role of genes in organizing behavior. Later in the book we discuss the role of environmental factors.
A striking illustration of how genes and environment interact is evident in phenylketonuria. This disease results in a severe impairment of cognitive function and
affects 1 child in 15,000. Children who express this disease have two abnormal copies of the gene that codes for phenylalanine hydroxylase, the enzyme that
converts the amino acid phenylalanine, a component of dietary proteins, to another amino acid, tyrosine. Many more children carry only one abnormal copy of
the gene and have no symptoms. Children who lack both functional copies of the gene build up high blood levels of phenylalanine. High blood levels of
phenylalanine in turn lead to the production of a toxic metabolite that interfereswith the normal maturation of the brain.1 Fortunately, the treatment for this
disease is remarkably simpleand effective: the mental retardation can be completely prevented by restricting protein intake, thereby reducing phenylalanine in
the diet.
Phenylketonuria is a particularly clear example of how an individual's phenotype depends on the interaction between genes and environment (Figure 3-1). In
phenylketonuria both heredity and environmental factors
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in the diet are clearly necessary for the expression ofthis form of mental retardation. A mere change in diet can rescue the genetic defect and the mental
functioning.

Figure 3-1 Heredity and environment are both necessary for the expression of phenylketonuria. (From Barondes 1995.)

In considering genetic factors that control behavior we need first to identify the components of behavior that are heritable. Clearly, behavior itself is not
inherited; what is inherited is DNA, which encodes proteins. The genes expressed in neurons encode proteins that are important for development, maintenance,
and regulation of the neural circuits that underlie all aspects of behavior. In turn, neural circuits are composed of many nerve cells, each of which expresses a
special constellation of genes that direct the production of specific proteins. For the development and function of a single neural circuit, a wide variety of
structural and regulatory proteins are required. In simple animals a single gene may control a behavioral trait by encoding a protein that affects the function of
individual nerve cells in a specific neural circuit. In more complex animals the circuitry is also more complex and behavioral traits are generally shaped by the
actions of many genes. Subtle differences in behavior can be achieved not only by the presence or absence of a given gene product or a set of products, but also
by the degree to which different gene products are expressed, or by the specific contribution of gene products.
The interplay of the genes, proteins, and neural circuits underlying behavior has been studied in various organisms ranging in complexity from worms and flies to
mice and humans. Molecular genetics provides the techniques to identify the genes involved in a particular behavior and to determine how the proteins they
encode control behavior. In worms, flies, and even in vertebrate organisms such as mice and zebrafish, it is possible to examine directly how genes influence
behavior because single-gene mutants of these organisms can be bred and isolated.
In this chapter we illustrate how the genetic dissection of behavior in simple animals can provide insight into the mechanisms that regulate human behavioral
traits. We then discuss a few important examples of the effects of single-gene defects on human behavior. Finally, we consider complex behavioral traits that
typically are determined by the actions of many genes.

Genetic Information Is Stored in Chromosomes
Genes contribute to the neural circuitry of behavior in two fundamental ways. First, through their ability to replicate reliably, each gene provides precise copies of
itself to all cells in an organism as well as succeeding generations of organisms. Second, each gene that is expressed in a cell directs the manufacture of specific
proteins that determine the structure, function, and other biological characteristics of the cell.
With rare exceptions, each cell in the human body contains precisely the same complement of genes, thought to be about 80,000. The reason cells differ from
one another—why one cell becomes a liver cell and another a brain cell—is that a distinct set of genes is expressed (as messenger RNA) in each cell type. Which
genes and proteins become activated in a particular cell depends on interactions between the molecules within the cell, between neighboring cells, and between
the cell and the organism's external environment (see Chapter 52). More of the total genetic information encoded in DNA—perhaps 30,000 of the 80,000
genes—is expressed in brain cells than in any other tissue of the body. Genes vary in size from 1 to 200,000 kilobases; the average size is about 10 kilobases.
The DNA of each gene that encodes a protein is made up of segments, called exons, which encode parts of the protein and these coding segments are interrupted
by noncoding segments called introns.
DNA is not distributed randomly within the nucleus but arranged in an orderly way on structures called chromosomes. The number of chromosomes varies among

different organisms. In addition, different types of organisms contain either one or two copies of each chromosome. With some exceptions, unicellular organisms
are haploid; they have only a single copy of each chromosome. By contrast, most complex multicellular organisms (worms, fruit flies, mice, and humans)
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are diploid; in all their somatic cells they carry two homologous copies of each chromosome and each gene, one from the mother and the other from the father.
The number of chromosomes in the germ, or sex, cells (sperm and egg) is half that found in somatic cells. During the nuclear division that accompanies somatic
cell division (the process of mitosis) the chromosomes are partitioned equally—each daughter cell receives one copy of each chromosome in the parent cell.
However, during the two successive nuclear divisions that accompany division of the germ cells (meiosis), the number of chromosomes is reduced by half.
Fertilization of the egg by the sperm restores the diploid number found in somatic cells, with homologous chromosomes contributed by each parent.
The 80,000 genes in the human genome are arranged in a precise order along the chromosomes. As a result, each gene is uniquely identifiable by its location at
a characteristic position (locus) on a specific chromosome. The two copies of a gene at corresponding loci on a pair of homologous chromosomes commonly
harbor sequence variations, or polymorphisms, at multiple sites throughout the gene. At any given site, the alternative gene versions are referred to as alleles.
Alleles may be identical or, more commonly, differ to some degree because of polymorphisms or mutations, as discussed below.
If two alleles are identical, the organism is said to be homozygous at that locus. If the alleles vary in form (in their nucleotide sequence), the organism is said to
be heterozygous at that locus. The recent DNA sequencing of a small number of human genes reveals large variance in the degree of intergenic polymorphism. In
general, however, the rate of polymorphic variation between any two individuals is estimated to be 1 per 1000 base pairs in noncoding DNA and 1 per 2000 base
pairs in coding DNA. Thus a 10 kilobase gene would harbor, on average, about 10 polymorphisms, including 1 or 2 in the coding sequence DNA. At each of these
polymorphic sites, an individual will carry at most two different forms of the same allele, whereas the same allele may exist in many forms within a population. A
difference within a population is called allelic polymorphism, or more generally, genetic polymorphism. Prominent examples of allelic polymorphism are the alleles
of the genes responsible for hair and eye color.
Humans have 46 chromosomes: 22 pairs of autosomes and two sex chromosomes (two X chromosomes in females, one X and one Y chromosome in males). The
parents contribute the sex chromosomes to their offspring differently from the manner they supply the autosomes. A spermatozoon carries either an X
(femaledetermining) or a Y (male-determining) chromosome, whereas an ovum carries only an X chromosome. As a consequence, males inherit their single X
chromosome from their mothers.
The 22 autosome pairs and the X and Y sex chromosomes vary in size and cytological banding pattern (Figure 3-2). Chromosome 1 is the largest autosome; it
contains 8% of the human genome, or about 6400 genes. Chromosome 22 is the smallest, containing 1% or about 800 genes. Chromosomes also vary in the
nucleotide sequence of their DNA, but paired autosomes are usually morphologically (cytogenetically) indistinguishable.

Gregor Mendel's Work Led to the Delineation of the Relationship Between Genotype and
Phenotype
The existence of alternative allelic forms of genes were discovered in 1866 by Gregor Mendel, who demonstrated the difference between dominant and recessive
alleles using garden peas as an experimental system. Mendel started out with self-breeding experiments on peas. These led to the creation of inbred strains of
peas that bred true for given characteristics of the pea such as color or the shape of the pod. He then crossed these inbred strains with each other and observed
how the various traits were manifested in the progeny of the pea plant. These crosses allowed Mendel to appreciate that the variability in heredity among the
progeny lay in differences in discrete factors that are passed unchanged from one plant generation to another, factors we now call genes. Moreover, Mendel
found that each pea had two sets of factors, one from the male parent and the other from the female.
Mendel carried out his studies before it was known how chromosomes behave during cell division. Forty years later it became clear that the segregation pattern
of genes noted by Mendel paralleled, almost exactly, the behavior of chromosomes during meiotic cell division, the division that produces the male and female
germ cells. These findings were used by Thomas Hunt Morgan to formulate the chromosomal theory of heredity, according to which each chromosome has a
linear array of unique genes running from one end to the other, each gene having a definite location on a particular chromosome.
While studying Mendel's results, Wilhelm Johannsen later distinguished between the genotype of an organism (its genetic makeup) and the phenotype of an
organism (its appearance). In the broad sense genotype refers to the entire set of alleles forming the genome of an individual; in the narrow sense it refers to
the specific alleles of one gene. Phenotype denotes the functional expression or consequences of a gene or set of genes. The phenotype of an individual may
change throughout life, whereas the genotype remains constant except for sporadic mutations.
Most mutations are simply allelic polymorphisms that are silent; that is, they do not have any effect on the phenotype. Some are not silent but are expressed in
ways that nevertheless appear neutral and therefore be-nign
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(Box 3-1). Benign mutations are allelic polymorphisms that produce differences in body type, such as eye color or hair color, as well as differences in personality
characteristics. The consequence of a mutation is often shaped by the environment. A mutation that favored a hunter-gatherer's survival during periodic food
shortages might lead to pathological obesity in a modern-day environment. Many mutations that do not have benign consequences, such as those leading to
excessive tallness, dwarfism, or color blindness, do not necessarily impair everyday functions. Some mutations may have significant consequences that are
limited to the cell-biological level, without any functional effects. An example would be a mutation that results in the failure of a single type of cell to develop in
an animal that can compensate for the loss of that cell type. Only rarely do mutations lead to significant changes in development, cell function, or overt behavior.
Some mutations are truly pathogenic, however, and these lead to human disease.

Figure 3-2 Map of normal human chromosomes at metaphase illustrating the distinctive morphology of each chromosome. (Adapted from Watson
et al. 1983.)

If a mutant phenotype results from one mutant allele in combination with one wild-type (normal) allele, the mutation or phenotypic trait is said to be dominant.
Dominant mutations usually lead to the production of an abnormal protein by the mutant allele or to the expression of the wild-type gene product at an
inappropriate time or place. Because they give rise to a new, perhaps toxic, variant of the protein or a new pattern of expression in the body, dominant
mutations are often referred to as gain of function mutations. Some dominant mutations produce an inactive protein product that can nevertheless interfere with
the function of the wild-type protein, thus leading to a complete loss of function of the gene. Such mutations are termed dominant negative mutations.
If a mutant phenotype is expressed only when both alleles of a gene are mutated (that is, only individuals
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homozygous for the mutant allele will exhibit the phenotype), the mutation or phenotypic trait is said to be recessive. Recessive mutations usually result from the
loss or reduction in amount of a functional protein. As a result, recessive mutations are often loss of function mutations. The reason both alleles need to be
defective in a recessive mutation in order for a phenotype to become evident is that a 50% reduction of most proteins (such as most enzymes) usually does not
cause serious (or even detectable) problems in cell function.

Box 3-1 The Origins of Genetic Diversity
Although DNA replication generally is carried out with high fidelity, spontaneous errors called mutations do occur. Mutations may result from damage to the
purine and pyrimidine bases, mistakes during the DNA replication process, and recombinations that occur between two nonhomologous chromosomes as a
result of errors in crossing over during meiosis. It is these mutations that give rise to genetic polymorphisms.
The rate of spontaneously occurring mutations is low. However, the frequency of mutations greatly increases when the organism is exposed to chemical
mutagens or ionizing radiation. Chemical mutagens tend to induce point mutations involving changes in a single DNA base pair or the deletion of a few base
pairs. By contrast, ionizing radiation can induce large insertions, deletions, or translocations. Both spontaneous and induced mutations can lead to changes
in the structure of the protein encoded by the gene (as in a dominant mutation) or to a partial decrease or absence of gene function or expression (as in
recessive mutations).
Changes in a single base pair involve one of three types of point mutations: (1) a missense mutation, where the point mutation results in one amino acid in
a protein being substituted for another; (2) a nonsense mutation, where a stop codon (triplet) is substituted for a codon within the coding region, thus
resulting in a shortened (truncated) protein product; or (3) a frameshift mutation, in which small insertions or deletions change the reading frame, leading to
the production of a truncated or abnormal protein.
Large-scale mutations involve changes in chromosome structure that can affect the function of many contiguous genes. Such mutations include
rearrangement of genes without the addition or deletion of material (inversion), duplication of genes in a chromosome, or the exchange (crossing over)
between segments of DNA. Sometimes large deletions of multiple genes occur. While these mutations are usually fatal if present in both copies of a gene
(homozygous lethals), they can result in phenotypes in the heterozygous state (such as the mental retardation associated with the Wilms tumor deletion
complex). Chromosomal translocation can also cause fusion between different (nonhomologous) chromosomes.

The Genotype Is a Significant Determinant of Human Behavior
Independent of Mendel's work, Francis Galton began to apply genetics to human behavior in 1869. In his book Hereditary Genius, Galton proposed that relatives
of individuals with extremely high mental ability were more likely to be endowed with similar abilities than would be predicted by chance: the closer the family
relationship, the higher the incidence of such gifted individuals.
Following Galton's initial insight, genetic studies of human behavior and disease have relied heavily on the analysis of kinship. Relatives share varying degrees of
genetic information and are classified as first degree (parents, siblings, and offspring), second degree (grandparents, grandchildren, nephews and nieces,
halfsiblings), third degree (first cousins), and so on, depending on the number of steps, more precisely the number of generations (meiotic events), separating
the members of the family tree.

Despite the uncontrolled nature of this early study, Galton was among the first to address the interplay of inheritance (nature) and environment (nurture) in the
determination of behavior. Galton was well aware that relatives of eminent individuals also share social, educational, and financial advantages, and that these
environmental factors might also account for the correlation between eminence and familial relationship. He therefore endeavored to assess more accurately the
relative contributions of heritable and environmental factors to behavioral traits. Thus, in 1883 he introduced the idea of the twin study, a method that today
remains a primary strategy for evaluating the role of genes and environment in complex behavioral traits.
Identical twins are monozygotic; they develop from a single zygote that splits into two soon after fertilization. As a result, identical twins share all genes; they
are as alike genetically as is possible for two individuals. In contrast, fraternal twins are dizygotic; they develop from two different fertilized eggs. Thus, dizygotic
twins, like normal siblings, share on average half their genetic information. Systematic comparisons of pairs of identical versus fraternal twins can be used to
assess the importance of genes in the development of a particular trait. If identical twins tend to be more similar (concordant) than fraternal twins, the trait is
attributable, at least in part, to genes.
The findings from such twin studies are further supP.41
ported by studies of identical twins that have been separated early in life and raised in different households. Despite sometimes great differences in their
environment, such twins share a remarkable number of behavioral traits that we normally consider to be distinctive features of individuality, such as intellectual,
religious, and vocational interests (Figures 3-3 and 3-4). Behavioral similarities between identical twins that have been separated at birth are attributable in part
to genes, although environmental factors may also play a role. In general, twin studies reinforce the idea that human conduct is shaped by genetic factors but do
not refute the role of environmental influences, which clearly exist.

Figure 3-3 Correlations among monozygotic twins reared together (MZT) and those reared apart (MZA) for physiological characteristics,
personality traits, interests, and attitudes. A score of zero represents no correlation—the average result for two random members of the population—while
a score of 1.0 represents a perfect correlation. Fingerprint ridge count, which is not expected to be subject to significant environmental influence, is virtually
identical in MZA and MZT pairs. Other characteristics, expected to be more subject to environmental influences, are not so highly correlated within each class.
Although the correlations for these characteristics are low, the results for MZT and MZA are similar. The correlations for the multidimensional personality scale
and religious attitudes among MZT and MZA are virtually identical, suggesting a significant, though not necessarily predominant, genetic influence on those
traits. Correlations for the occupational interest scale and nonreligious social attitudes among MZA and MZT are more different between the two groups. (Based
on Bouchard et al. 1990.)

The environmental contribution to behavioral traits is often divided into shared and nonshared components. Shared environmental influences, such as childrearing practices or income, may underlie observed phenotypic similarities among family members. In contrast, nonP.42
shared influences, such as interactions with peers in school, can create differences among members of the same family. As discussed below, similarities in
personality between biological relatives are due primarily to genetic components, with differences arising from genetic factors and nonshared environmental
factors.

Figure 3-4 Variation in personality in studies of twins. The units express the degree of variance accounted for by various genetic and environmental
influences. (Based on Bouchard 1994.)

Although studies of identical twins and kinships provide strong support for the idea that human behavior has a significant hereditary component, they do not tell
us how many genes are important, let alone how specific genes affect behavior. These questions can be addressed by genetic studies in experimental animals in
which both the gene and the environment are strictly controlled and by studies of human genetic mutations that give rise to diseases.

Single Gene Alleles Can Encode Normal Behavioral Variations in Worms and Flies
A number of studies of natural populations of flies and worms have found that allelic polymorphisms in single genes can contribute to individual differences in
naturally occurring behavior, including social behavior. The first example was provided by Ron Kondoka and his colleagues, who found variants in the circadian
rhythm of flies as a result of molecular polymorphisms in the period gene. Wild-type flies vary in how well they can maintain their circadian rhythm in the
presence of a temperature change, a feature called temperature compensation. As we will discuss below, the protein products of the period and timeless genes
are involved in an autoregulatory feedback that is critical for circadian rhythms. The per gene has a repeat region of threonine-glycine that is polymorphic in
length. Two of the major variants (with 17 repeats and 20 repeats) are found in Europe along a north-south cline. Flies with long repeats are better able to
compensate for temperature shifts than those with short repeats.

A second example of such individual differences was discovered by Marta Sokolowski and her colleagues while examining the natural variation in the foraging
behavior of fly larvae. Some larvae are rovers and others are sitters. Rovers follow longer foraging paths, whereas sitters use much smaller paths. The rover
larvae also tend to move between patches of food, while the sitters tend to remain feeding within a food pack. This difference between rovers and sitters results
from a single gene called forager. The rover allele has complete dominance over the sitter allele. In nature there are 70% rovers and 30% sitters. In fact, sitter
larvae can be converted to rover larvae by expressing in them the gene encoding the rover phenotype. The forager gene encodes a cGMP-dependent protein
kinase whose activities are higher in rover than in natural sitters, or sitter mutants, which suggests that the protein kinase may be regulated differently in the
two natural variants.
Single genes can even account for differences in normal social behavior. In the course of studying 22 natural isolates of the nematode worm Caenorhabditis
elegans collected from various locations around the world, Jonathan Hodgkin and Tabitha Doniach had found that, when grown on the surface of agar-filled Petri
plates seeded with Escherichia coli, these natural isolates distributed themselves on the agar surface in two ways. Half the strains dispersed evenly across the
bacterial patch, but the other strains spontaneously formed large, dense aggregates called clumps. This clumping arises, at least in part, from interaction among
the worms in the clump. Mario deBono and Cornelia Bargmann realized that this reflected an example of individual differences in social behavior. They called the
dispersing strains solitary and the clumping strains social.
Bargmann and deBono have identified natural variants in the behavior of worms feeding on E. coli in a Petri dish. Some worms are solitary foragers, moving
across the food and feeding alone, while others are social foragers aggregating together on the food while they feed. More than 50 percent of the social foragers
are found in groups, whereas less than two percent of the solitary foragers are found in groups. The social worms may aggregate due to the presence of a
mutually attractive, as yet unidentified stimulus.
DeBono and Bargmann gathered social strains of worms that arose from mutagenesis screens of solitary strains in several laboratories and found that the
mutation encodes for a gene that resembles the neuropeptide Y receptor, a G protein-coupled receptor that is ubiquitous and important in mammals for feeding.
Genetic analysis of normal, wild-type strains showed that the difference between social and solitary strains was due to the substitution of a single amino acid in a
cytoplasmic loop of the neuropeptide Y receptor gene. Neuropeptides are found in the brain along with conventional small molecules and are often involved in
regulating responses over long periods of time. Since neuropeptide Y receptors are associated with feeding and appetite in mammals, it raises the intriguing
possibility that closely related peptides might control foraging and eating behaviors in a variety of organisms that are evolutionarily divergent.

Mutations in Single Genes Can Affect Certain Behaviors in Flies
The influence of genes on behavior can be explored most rigorously in simple animals, such as the fruit fly
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Drosophila. Mutations of single genes in Drosophila can produce abnormalities in learned as well as innate behaviors, such as courtship and circadian rhythms.
Moreover, mutations that affect specific aspects of behavior can readily be induced in flies (Box 3-2).

Box 3-2 Introducing Transgenes in Flies and Mice
Genes can be manipulated in mice by injecting DNA into the nucleus of newly fertilized eggs (Figure 3-5). In some of the injected eggs the new gene, or
transgene, is incorporated into a random site on one of the chromosomes and, since the embryo is at the one-cell stage, the incorporated gene is replicated
and ends up in all (or nearly all) of the animal's cells, including the germline.
Gene incorporation is most easily detected by coinjecting the marker gene for pigment production into an egg obtained from an albino strain. Mice with
patches of pigmented fur indicate successful expression of DNA. The transgene's presence is confirmed by testing a sample of DNA from the injected
individuals.
A similar approach is used in flies. The DNA need not be injected directly into a nucleus since the vector used, called a P element, is capable of being
incorporated into germ cell nuclei at the time the first cells form in the embryo. The development and function of the nervous system of flies can be altered
using promoters that are expressed ubiquitously, such as the inducible heat-shock promoter hsp70 in Drosophila. More specific patterns of expression in
brain cells can be obtained using promoter and enhancer sequences from genes that are specific to a cell type.
Transgenes may be wild-type genes that rescue a mutant phenotype or novel “designer” genes that drive expression of a gene in new locations or produce a
specifically altered gene product.

Figure 3-5 Standard procedures for generating transgenic mice and flies. Here the gene injected into the mouse causes a change in coat color,
while the gene injected into the fly causes a change in eye color. In some transgenic animals of both species the DNA is inserted at different chromosomal
sites in different cells (see illustration at bottom). (From Alberts et al. 1994.)

The genetic analysis of the behavior of flies has its origins in the behavioral screens performed in the 1970s by Seymour Benzer and his colleagues. These
screens detected and isolated mutations that affect circadian (daily) rhythms, courtship behavior, movement, visual perception, and memory. The powerful
techniques of Drosophila molecular genetics have enabled investigators to identify these genes and characterize how their protein products act. Here we shall
focus on one class of genes isolated by Benzer, those that affect circadian rhythms. In Chapter 63 we shall consider genes in Drosophila that influence memory.
Many aspects of animal physiology and behavior fluctuate in rhythmic cycles. Most of these rhythms follow a circadian period; others follow shorter-term
(ultradian) periods. Circadian clocks are thought to have a significant adaptive advantage. For example, they provide a means of anticipating dawn and thereby
coordinate physiological functions with environmental conditions. Circadian rhythms affect everything from locomotor activity to mood and play a major role in
the biology of motivation (see Chapter 51). Because of the ubiquity of these clocks among animals (and even fungi), experimental advances in invertebrates
should aid in our understanding of human circadian behaviors.
Clocks have three basic features. First, the core of the clock is an intrinsic oscillator capable of producing a circadian periodicity of approximately 24 hours.
Second, this intrinsic oscillator can adapt its rhythm to changes in the duration of the day-night cycle throughout the year. This regulation is primarily achieved
through various light-driven signals that are transmitted by the eye to the brain, where the signals in turn act on the oscillator. Third, there are a set of output
pathways from the oscillator that control specific behaviors, such as sleep and wakefulness and locomotor activity.
Mutations altering biological rhythms have been isolated in several organisms. The greatest insight into the oscillator has been obtained from studies of two
genes in Drosophila, the period (per) gene, identified originally by Benzer and his colleagues, and the timeless (tim) gene identified recently. The period and
timeless genes appear to be devoted almost exclusively to the control of rhythms. Even when they are eliminated, the organism has no other major defects.
Mutations in either the per or tim gene affect the circadian rhythms of locomotor activity and eclosion (ie, the emergence of the adult from the pupa). Arrhythmic
per mutants exhibit no discernible rhythms in either of these behaviors. A long-day per allele produces 28-hour cycles for both locomotor activity and eclosion,
whereas two short-day per alleles shorten the cycle (to 19 hours in one case and to 16 hours in the other; see Figure 3-6).
How do the per and tim genes keep time? The answer to this question has begun to emerge from genetic and molecular studies of the two genes and their
protein products. The protein products of the per and tim genes (PER and TIM) are thought to shuttle between the cytoplasm and nucleus of cells, regulating
expression of target genes, including themselves. As a result, the synthesis and accumulation of the messenger RNAs encoding PER and TIM follow a circadian
cycle.
For the proteins to function, PER has to bind to TIM (Figure 3-7). Both genes are transcribed in the morning and their mRNAs accumulate during the day, during
which the protein products appear not to be functional. A key step in the regulation of this cycle is the light-induced degradation of the TIM protein. During the
day tim RNA is transcribed but the level of TIM protein remains low because of a high rate of degradation. In the absence of TIM, PER does not function. As a
result, TIM and PER complexes are not formed. After dusk, when the levels of TIM and PER increase, the two proteins bind to one another, thus becoming
functional, and enter the nucleus where they inhibit the transcription of their own genes as well as other, unidentified target genes. As a consequence, per and
tim mRNAlevels decrease and subsequently protein expression decreases. By morning, PER and TIM protein levels have fallen to low enough levels that they no
longer repress transcription.
The finding that the per and tim transcripts are regulated by negative feedback raises the question of why the PER and TIM proteins do not immediately repress
their own expression. The answer lies in a builtin delay in accumulation and translocation of the proteins to the nucleus. The PER protein cannot accumulate until
sufficient TIM protein is present to bind to and stabilize it. TIM protein, on the other hand, cannot enter the nucleus unless it is bound to PER protein. Accurate
time-keeping therefore depends on an oscillatory cycle in gene expression and inactivation by negative feedback.
What does this say for mechanisms in normal and short-cycle flies? In the long-day (28-hour) per mutants the binding affinity of PER proteins for TIM appears to
be reduced. Binding thus cannot occur until the two proteins reach higher levels, causing a delay in the entry of the PER-TIM complex into the nucleus and thus
extending the period of each cycle.
The mechanisms that control circadian rhythms in other organisms are likely to be similar in principle to
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the mechanism that controls the rhythmicity of the per and tim genes in Drosophila. In mammals circadian behavioral rhythms are governed by the
suprachiasmatic nucleus in the hypothalamus (see Chapter 47). Because circadian behavior in mice is precise, it is easy to set up quantitative genetic screens for
mutations that alter the circadian behavior. Joseph Takahashi took advantage of the regularity of this behavior to carry out a chemical mutagenesis screen. By
this means he identified a semidominant autosomal mutation named clock. Mice homozygous for the clock mutation show extremely long circadian periods
followed by a complete loss of circadian rhythmicity when transferred to constant darkness (Figure 3-8). The clock gene therefore appears to regulate two
fundamental properties of the circadian rhythm in mice: the circadian period itself and the persistence of circadian rhythmicity.

Figure 3-6 A single gene, period (per), governs the circadian rhythms of specific behaviors in Drosophila. (From Konopka and Benzer 1971.)
A. Locomotor rhythms in normal Drosophila and three per mutant strains: short-day, long-day, and arrhythmic. Flies were exposed to a cycle of 12 hours of
light and 12 hours of darkness, and activity was then monitored under infrared light. Heavy lines indicate activity.
B. Normal adult fly populations emerge from their pupal cases in cyclic fashion, even in constant darkness. The plots show the number of flies (in each of four
populations) emerging per hour over a 4-day period of constant darkness. The arrhythmic per mutant population emerges without any discernible rhythm.

Since no anatomical defects have been observed with the clock mutation, the clock gene appears to encode a protein specific and essential for circadian
rhythmicity in the mouse. When the clock gene was cloned it was found to encode a transcription factor, presumably involved in the basic regulation of genes
important for the circadian rhythm. Particularly important is the fact that one of the domains of the clock protein (the PAS domain) is also found in PER. This
raises the interesting possibility that the clock protein might bind to and interact with a mouse protein homologous to PER. Many mammalian genes related to
clock have now been identified and implicated in the control of circadian rhythms.

Figure 3-7 Light-dependent degradation of the TIM protein establishes the circadian control of biological rhythms in Drosophila. The genes that
control the circadian clock are regulated by two nuclear proteins, PER and TIM, that slowly accumulate and then bind to one another to form dimers.
Dimerization of PER and TIM is necessary for the complex to enter the nucleus and shut off the transcription of target genes, including the genes for PER and
TIM themselves. During the hours of daylight TIM protein is degraded by light; thus PER cannot enter the nucleus and the transcription of target genes
(including the per and tim genes) continues. After dark, TIM protein is no longer degraded, and the PER-TIM dimers enter the nucleus, where they repress
transcription of target genes. In this way the daynight cycle regulates the expression of genes that control biological function. (Adapted from Barinaga 1996.)

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Defects in Single Genes Can Have Profound Effects on Complex Behaviors in Mice
The use of chemical genetic techniques to identify circadian rhythm mutants in mice underscores the importance of this experimental mammal in behavioral
genetic studies. Genetic studies of mouse behavior have begun to provide insight into the genetic bases of some human behavioral disorders. Here we discuss
the evidence for a genetic basis for three disorders: obesity, impulsivity, and altered motivational state.

Mutations in the Gene Encoding Leptin Affect Feeding Behavior
Whether an individual is lean, obese, or of intermediate size is determined in large part by the balance between the amount of food consumed and energy
expended, a balance governed by both psychological and physiological factors. Genetics studies of obese mice have provided the best insight into the
physiological factors that control ingestive behavior.
The physical cloning and characterization of the region around a spontaneous obesity-causing mutation on mouse chromosome 6 led to the identification of the
mouse obese (ob) gene and to a highly conserved (homologous) human gene. The mouse ob gene encodes the protein leptin, a small protein of 145 amino acids
that is selectively expressed in adipose tissue and released into the bloodstream. Leptin contributes to the homeostatic mechanisms that permit an animal to
maintain its weight within 5% of its normal weight for most of its life. Under normal conditions the amount of leptin secreted reflects the total mass of adipose
tissue. When adipose tissue decreases, leptin levels decrease and the animal eats more; when adipose tissue increases, leptin levels increase and the animal eats
less. Mice with homozygous mutations in the ob gene lack circulating leptin. This lack leads to marked obesity in these mutant animals. When leptin is supplied
exogenously, however, food intake and body weight are reduced dramatically.
Areceptor for leptin, called OB-R, encodes a protein that is related to a component of certain cytokine receptors that activate specific transcription factors. This
leptin receptor is expressed at a high level in the hypothalamus, the part of the brain that controls appetite and feeding (Chapter 32). The gene encoding OB-R is
located in the same region of mouse chromosome as the diabetic gene (db). This is interesting because obesity and diabetes are often linked in humans. In fact,
db/db mice are also obese and exhibit a phenotype similar to the mice with a mutated ob gene. Moreover, there is good evidence that the db gene encodes the
leptin receptor.

Figure 3-8 Locomotor activity records of clock mutant mice. The record shows periods of wheel-running activity by three offspring. All animals were kept
on a light-dark cycle (L/D) of 12 hours for the first 7 days, then transferred to constant darkness (D). They later received a 6-hour light pulse (LP) to reset the
rhythm. The activity rhythm for the wild-type mouse had a period of 23.1 hours. The period for the heterozygous clock/+ mouse is 24.9 hours. The homozygous
clock/clock mice experience a complete loss of circadian rhythmicity upon transfer to constant darkness and transiently express a rhythm of 28.4 hours after the
light pulse. (From Takahashi et al. 1994.)

To what extent do these studies of mice provide insight into human disease? Most obese humans are not defective in leptin mRNA or protein levels and indeed
produce higher levels than do nonobese individuals. Thus, it is likely that human obesity reflects not a lack of leptin but a failure to respond to normal or even
elevated levels of leptin. Failure to respond to leptin could be a result of mutations of the leptin receptor or of molecules that interact with the receptor.
Leptin may affect feeding behavior by regulating neuropeptide and neurotransmitter expression in hypothalamic cells. Lesions of the hypothalamus affect body
weight. For example, ablation of the ventromedial hypothalamus or the arcuate nucleus results in obesity. Leptin administration markedly inhibits the
biosynthesis and release of neuropeptide Y, a peptide that stimulates food
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intake when administered to rodents. Remarkably, as we have discussed earlier, the link between neuropeptide Y and food intake appears to have been
conserved, in a general sense, between C. elegans and man.

Box 3-3 Generating Mutations in Flies and Mice
Flies
Genetic analysis of behavior in Drosophila relies on behavioral assays of animals in which individual genes have been mutated. Experimental mutations in
Drosophila were originally produced through radiation-induced mutagenesis. This method, however, results in large-scale deletions or rearrangements in
chromosomes; several genes are often affected, even when small deletions are the target, and molecular characterization of relevant genes is difficult. In
contrast, the chemical ethyl methanesulfonate (EMS) induces point mutations and thus facilitates the characterization of mutations at specific loci.
Many spontaneous mutations and chromosomal rearrangements are produced by transposable elements. The most useful class of transposable elements in
Drosophila is the P element. P elements encode a transposase enzyme that mediates the mobilization of the element and a repressor product that blocks
transposition. P elements have become major tools of the modern Drosophila geneticist.
In one technique, P elements are used to isolate mutations in any Drosophila gene of interest. The investigator screens for mutants of the gene in progeny of
crosses between Drosophila strains that carry P elements and those in which they are absent. New mutations result from the transposition of a P element
into a gene. A vector is then constructed in which a P element is inserted. This vector is used as a probe to identify and isolate DNA segments that contain P
elements; elements inserted into the gene of interest are found within a subset of these segments. The gene can then be cloned and studied.

Mice
Recent advances in molecular manipulation of mammalian genes have permitted in situ replacement of a known, normal gene with a mutant version. The
process of generating a strain of mutant mice involves two separate manipulations: the replacement of a gene on a chromosome by homologous
recombination in a special cell line known as embryonic stem cells (Figure 3-9), and the subsequent incorporation of this modified cell line into the germ cell


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