The Student’s Guide to Cognitive Neuroscience 2020 PDF

The Student’s Guide to Cognitive Neuroscience Reflecting recent changes in the way cognition and the brain are studied, this thoroughly updated fourth edition of this bestselling textbook provides a comprehensive and student-friendly guide to cognitive neuroscience. Jamie Ward provides an easy-to-...

The Student’s Guide to Cognitive Neuroscience Reflecting recent changes in the way cognition and the brain are studied, this thoroughly updated fourth edition of this bestselling textbook provides a comprehensive and student-friendly guide to cognitive neuroscience. Jamie Ward provides an easy-to-follow introduction to neural structure and function, as well as all the key methods and procedures of cognitive neuroscience, with a view to helping students understand how they can be used to shed light on the neural basis of cognition. The book presents a comprehensive overview of the latest theories and findings in all the key topics in cognitive neuroscience, including vision, hearing, attention, memory, speech and language, numeracy, executive function, social and emotional behavior and developmental neuroscience. Throughout, case studies, newspaper reports, everyday examples and student- friendly pedagogy are used to help students understand the more challenging ideas that underpin the subject. New to this edition: Increased focus on the impact of genetics on cognition New coverage of the cutting-edge field of connectomics Coverage of the latest research tools including tES and fNIRS and new methodologies such as multi-voxel pattern analysis in fMRI research Additional content is also included on network versus modular approaches, brain mechanisms of hand–eye coordination, neurobiological models of speech perception and production and recent models of anterior cingulate function. Written in an engaging style by a leading researcher in the field and presented in full color including numerous illustrative materials, this book will be invaluable as a core text for undergraduate modules in cognitive neuroscience. It can also be used as a key text on courses in cognition, cognitive neuropsychology, biopsychology or brain and behavior. Those embarking on research will find it an invaluable starting point and reference. This textbook is supported by an extensive companion website for students and instructors, including lectures by leading researchers, links to key studies and interviews, interactive multiple-choice questions and flashcards of key terms. Jamie Ward is Professor of Cognitive Neuroscience at the University of Sussex, UK. He is the author of a number of books on social and cognitive neuroscience and on synesthesia, and is President of the British Association of Cognitive Neuroscience. The Student’s Guide to Cognitive Neuroscience To find additional tools to master the concepts and terminology covered in The Student’s Guide to Cognitive Neuroscience, visit the companion website for the fourth edition, available at: www.routledge.com/cw/ward What you will find on this website: For students: Videos and links to interviews, lectures, documentaries, and studies Simulations of key experiments Interactive multiple-choice quizzes for each chapter Flashcards to test your knowledge of key terms. For instructors: Lecture guides Downloadable PowerPoint teaching slides Additional quiz questions and answers. THE STUDENT’S GUIDE TO COGNITIVE ­NEUROSCIENCE Fourth Edition JAMIE WARD Fourth edition published 2020 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN and by Routledge 52 Vanderbilt Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2020 Jamie Ward The right of Jamie Ward to be identified as author of this work has been asserted by him in accordance with Sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. First edition published by Psychology Press 2006 Third edition published by Psychology Press 2013 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record has been requested for this book ISBN: 978-1-138-49052-9 (hbk) ISBN: 978-1-138-49054-3 (pbk) ISBN: 978-1-351-03518-7 (ebk) Typeset in Times New Roman by Swales & Willis Ltd, Exeter, Devon, UK Visit the companion website: www.routledge.com/cw/ward Contents About the author ix Preface to the fourth edition xi 1 Introducing cognitive neuroscience 1 Cognitive neuroscience in historical perspective 2 Does cognitive psychology need the brain? 10 Does neuroscience need cognitive psychology? 12 From modules to networks 13 2 Introducing the brain 19 Structure and function of the neuron 19 The gross organization of the brain 24 The cerebral cortex 28 The subcortex 30 The midbrain and hindbrain 32 3 The electrophysiological brain 35 In search of neural representations: single-cell recordings 36 Electroencephalography and event-related potentials 41 Mental chronometry in electrophysiology and cognitive psychology 46 Magnetoencephalography 52 4 The imaged brain 55 Structural imaging 56 Functional imaging 58 From image to cognitive theory: experimental design 63 Analyzing data from functional imaging 72 Interpreting data from functional imaging 75 Why do functional imaging data sometimes disagree with lesion data? 77 Brain-reading: is “Big Brother” round the corner? 80 vi CONTENTS 5 The lesioned brain and stimulated brain 87 Dissociations and associations in neuropsychology 90 Single-case studies in cognitive neuropsychology 93 Group studies and lesion-deficit analysis in neuropsychology 97 Animal models in neuropsychology 100 Transcranial magnetic stimulation (TMS) 102 Transcranial electrical stimulation (tES) 110 6 The developing brain 115 Structural development of the brain 118 Functional development of the brain 122 Nature and nurture of individual differences 129 7 The seeing brain 143 From eye to brain 144 Cortical blindness and “blindsight” 149 Functional specialization of the visual cortex beyond V1 152 Recognizing objects 156 Recognizing faces 164 Vision imagined 171 8 The hearing brain 175 The nature of sound 177 From ear to brain 178 Basic processing of auditory information 181 Music perception 186 Voice perception 191 Speech perception 193 9 The attending brain 203 Spatial and non-spatial attentional process 204 The role of the frontoparietal network in attention 208 Theories of attention 217 Neglect as a disorder of spatial attention and awareness 224 10 The acting brain 233 A basic cognitive framework for movement and action 234 The role of the frontal lobes in movement and action 235 Ownership and awareness of actions 242 Action comprehension and imitation 246 Acting on objects 249 Fronto-striatal and cerebellar networks in action 258  CONTENTS vii 11 The remembering brain 265 Short-term and working memory 266 Different types of long-term memory 271 Amnesia 273 Functions of the hippocampus and medial temporal lobes in memory 279 Theories of remembering, knowing and forgetting 287 The role of the prefrontal cortex in long-term memory 292 12 The speaking brain 299 Spoken word recognition 301 Semantic memory and the meaning of words 307 Understanding and producing sentences 316 Retrieving and producing spoken words 323 13 The literate brain 331 Visual word recognition 334 Reading aloud: routes from spelling to sound 341 Spelling and writing 352 Does spelling use the same mechanisms as reading? 356 14 The numerate brain 359 Universal numeracy? 360 The meaning of numbers 362 Models of number processing 374 15 The executive brain 385 Anatomical and functional divisions of the prefrontal cortex 387 Executive functions in practice 390 The organization of executive functions 398 The role of the anterior cingulate in executive functions 411 16 The social and emotional brain 415 Theories of emotion 416 Neural substrates of emotion processing 424 Reading faces 434 Understanding other minds 440 References451 Author index 515 Subject index 517  About the author Jamie Ward is Professor of Cognitive Neuroscience at the University of Sussex, UK. He completed degrees at the University of Cambridge (1991–1994) and the University of Birmingham (1994–1997). He subsequently worked as a Research Fellow at the University of Sussex (1997–1999) and as Lecturer and Senior Lecturer at University College London (1999–2007). His principal research interest lies in the cognitive neuroscience of synesthesia, although he has published on many other topics, including frontal lobe function, memory and disorders of reading and spelling. His research uses a number of methods in cognitive neuroscience, including human neuropsychology, functional imaging, EEG and TMS. His other books include The Frog Who Croaked Blue: Synesthesia and the Mixing of the Senses and The Student’s Guide to Social Neuroscience. He is the founding editor of the journal, Cognitive Neuroscience, and is currently President of the British Association of Cognitive Neuroscience (BACN).  Preface to the fourth edition The motivation for writing this book came out of my experiences of teaching cognitive neuroscience. When asked by students which book they should buy, I felt that none of the existing books would satisfactorily meet their needs. Other books in the market were variously too encyclopedic, too advanced or not up to date, or gave short shrift to explaining the methods of the field. My brief for writing this textbook was to provide a text that presents key ideas and findings but is not too long, that is up to date and that considers both method and theory. I hope that it will be useful to both lecturers and students. In writing a book on cognitive neuroscience I had to make a decision as to how much would be “cognitive” and how much would be “neuroscience.” In my opinion, the theoretical underpinnings of cognitive neuroscience lie within the cognitive psychology tradition. Some of the most elegant studies using methods such as fMRI and TMS have been motivated by previous research in cognitive psychology and neuropsychology. The ultimate aim of cognitive neuroscience is to provide a brain-based account of cognition, and so the methods of cognitive neuroscience must necessarily speak to some aspect of brain function. However, I believe that cognitive neuroscience has much to learn from cognitive psychology in terms of which theoretically interesting questions to ask. In Chapter 1, I discuss the current status of cognitive neuroscience as I see it. Some of the topics raised in this chapter are directly aimed at other researchers in the field who are skeptical about the merits of the newer methodologies. I suspect that students who are new to the field will approach the topic with open-mindedness rather than skepticism, but I hope that they will nevertheless be able to gain something from this debate. Chapter 2 is intended primarily as a reference source that can be referred back to. It is deliberately pitched at a need-to-know level. Chapters 3 to 5 describe in detail the methods of cognitive neuroscience. The aim of an undergraduate course in cognitive neuroscience is presumably to enable students to critically evaluate the field and, in my opinion, this can only be achieved if the students fully understand the limitations of the methods on which the field is based. I also hope that these chapters will be xii PREFACE TO THE FOURTH EDITION of use to researchers who are starting out in the field. This fourth edition has been updated to include the latest research tools (such as tES, transcranial electrical stimulation) and the latest research methodology (such as multi- voxel pattern analysis, MVPA, in fMRI research). Chapters 6 to 16 outline the main theories and findings in the field. I hope that they convey something of the excitement and optimism that currently exists. This fourth edition represents a substantial update. The order of the chapters has been changed to bring development much earlier on (as it deals with general issues relating to brain structure and function). These chapters were also extensively updated to take into account the rapid changes in this field, notably the links with genetic methods and connectomics. Vision and hearing are now consecutive chapters (Chapters 7 and 8), which link well to the following chapters on attention and action. The following topics have either been added for the first time or extensively updated: network versus modular approaches (Chapter 1), magnetoencephalography (MEG) (Chapter 3), functional near-infrared spectroscopy (fNIRS) (Chapter 4), visual imagery (Chapter 7), parietal lobe mechanisms of sensorimotor transformation (Chapter 10), recent neurobiological models of speech perception and production (Chapter 12), developmental dyslexia (Chapter 13) and the neuroscience of racial biases (Chapter 16). In addition, we have created a demonstration library of cognitive tests (www.testable.org/ward) with thanks to Constantin Rezlescu. Within the textbook, we provide more guidance to web resources via new feature boxes in the text, as well as via our dedicated webpage (www.routledge.com/cw/ward). Jamie Ward [email protected] Brighton, UK, March 2019 CH A P TE R 1 Introducing cognitive neuroscience CONTENTS Cognitive neuroscience in historical perspective 2 Does cognitive psychology need the brain? 10 Does neuroscience need cognitive psychology? 12 From modules to networks 13 Summary and key points of the chapter 16 Example essay questions 16 Recommended further reading 17 Between 1928 and 1947, Wilder Penfield and colleagues carried out a series of remarkable experiments on over 400 living human brains (Penfield & Rasmussen, 1950). The patients in question were undergoing brain surgery for epilepsy. To identify and spare regions of the brain involved in movement and sensation, Penfield electrically stimulated regions of the cortex while the patient was still conscious. The procedure was not painful (the surface of the brain does not contain pain receptors), but the patients did report some fascinating experiences. When stimulating the occipital lobe one patient reported, “a star came down toward my nose.” Upon stimulating a region near the central sulcus, another patient commented, “those fingers and my thumb gave a jump.” After temporal lobe stimulation, another patient claimed, “I heard the music again; it is like the radio.” She was later able to recall the tune she heard and was absolutely convinced that there must have been a radio in the operating theatre. Of course, the patients had no idea when the electrical stimulation was being applied—they couldn’t physically feel it or see it. As far as they were concerned, an electrical stimulation applied to the brain felt pretty much like a mental/cognitive event. This book tells the emerging story of how mental processes such as thoughts, memories and perceptions are organized and implemented by the  2 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE FIGURE 1.1: A timeline for the development of methods 1800 Phrenologists put forward their localizationist manifesto and findings relevant to 1820 cognitive neuroscience, from phrenology to present day. 1840 First nerve cell described (purkinje, 1837) 1860 Broca (1861) publishes paper on language localization Applying electrical currents to dog cortex causes movement 1880 (Fritsch & Hitzig, 1870) 1900 EEG developed as a research tool (Berger, 1929) Action potential discovered, enables single-cell recording 1920 (Hodgkin & Huxley, 1939) Cognitive psychology emerges (influential publications by 1940 Broadbent, Chomsky, Miller and others) 1960 CT (Hounsfield, 1973) and MRI (Lauterbur, 1973) imaging developed in vivo blood flow measured in humans, enabling PET (Reivich et al., 1979) 1980 First study of TMS reported (Barker et al., 1985) 2000 BOLD response reported enabling fMRI development (Ogawa et al., 1990) 2010 Attempt to map all major connections of the brain (Human Connectome Project) brain. It is also concerned with how it is possible to study the mind and brain, and how we know what we know. The term cognition collectively refers to a variety of higher mental processes such as thinking, perceiving, imagining, ONLINE RESOURCES speaking, acting and planning. Cognitive neuroscience is a bridging discipline between cognitive science and cognitive psychology, on the one To discover more about Wilder Penfield hand, and biology and neuroscience, on the other. It has emerged as a distinct and his pioneering enterprise only recently and has been driven by methodological advances that research, watch the enable the study of the human brain safely in the laboratory (see Figure 1.1). videos found on the It is perhaps not too surprising that earlier methods, such as direct electrical companion website stimulation of the brain, failed to enter into the mainstream of research. (www.routledge.com/ cw/ward). This chapter begins by placing a number of philosophical and scientific approaches to the mind and brain in a historical perspective. The coverage is selective rather than exhaustive, and students with a particular interest K EY TERMS in these issues might want to read more deeply elsewhere (Wickens, 2015). The chapter then provides a basic overview of the current methods used Cognition A variety of higher in cognitive neuroscience. A more detailed analysis and comparison of the mental processes such different methods is provided in Chapters 3 to 5. Finally, the chapter attempts as t­hinking, perceiving, to address some of the criticisms of the cognitive neuroscience approach that imagining, speaking, have been articulated and outlines how it can move forward. acting and planning. Cognitive neuroscience C O G N I T I V E N E UROSCIE NCE IN HISTORICAL Aims to explain cognitive processes in terms of PER S PEC T I V E brain-based mechanisms. Philosophical approaches to mind and brain Mind–body problem The problem of how a Philosophers, as well as scientists, have long been interested in how the brain physical substance (the can create our mental world. How is it that a physical substance can give brain) can give rise to our rise to our sensations, thoughts and emotions? This has been termed the sensations, thoughts and mind–body problem, although it should more properly be called the mind– emotions (our mind). brain problem, because it is now agreed that the brain is the key part of  Introducing cognitive neuroscience 3 the body for cognition. One position is that the mind and brain are made KEY TERMS up of different kinds of substance, even though they may interact. This is known as dualism, and the most famous proponent of this idea was René Dualism The belief that mind Descartes (1596–1650). Descartes believed that the mind was non-physical and brain are made up and immortal whereas the body was physical and mortal. He suggested that of different kinds of they interact in the pineal gland, which lies at the center of the brain and substance. is now considered part of the endocrine system. According to Descartes, Dual-aspect theory stimulation of the sense organs would cause vibrations in the body/brain that The belief that mind and would be picked up in the pineal gland, and this would create a non-physical brain are two levels of sense of awareness. There is little hope for cognitive neuroscience if dualism is description of the same true because the methods of physical and biological sciences cannot tap into thing. the non-physical domain (if such a thing were to exist). Reductionism Even in Descartes’ time, there were critics of his position. One can The belief that mind- identify a number of broad approaches to the mind–body problem that still based concepts will have a contemporary resonance. Spinoza (1632–1677) argued that mind and eventually be replaced by brain were two different levels of explanation for the same thing, but not two neuroscientific concepts. different kinds of thing. This has been termed dual-aspect theory and it remains popular with some current researchers in the field (Velmans, 2000). An analogy can be drawn to wave–particle duality in physics, in which the same entity (e.g., an electron) can be described both as a wave and as a particle. An alternative approach to the mind–body problem that is endorsed by many contemporary thinkers is reductionism (Churchland, 1995; Crick, 1994). This position states that, although cognitive, mind-based concepts (e.g., emotions, memories, attention) are currently useful for scientific exploration, they will eventually be replaced by purely biological constructs (e.g., patterns of neuronal firings, neurotransmitter release). As such, psychology will eventually reduce to biology as we learn more and more about the brain. Advocates of this approach note that there are many historical precedents in which scientific constructs are abandoned when a better explanation is found. In the seventeenth century, scientists believed that flammable materials contained a substance, called phlogiston, which was released when burned. This is similar to classical notions that fire was a basic element along with water, air and earth. Eventually, this construct was replaced by an understanding of how chemicals combine with oxygen. The process of burning became just one example (along with rusting) of this particular chemical reaction. Reductionists believe that mind-based concepts, and conscious experiences in particular, will have the same status as phlogiston in a future theory of the brain. Those who favor dual-aspect theory over reductionism point out that an emotion would still feel like an emotion even if we were to fully understand its neural basis and, as such, the usefulness of cognitive, mind-based concepts will never be fully replaced. Scientific approaches to mind and brain Our understanding of the brain emerged historically late, largely in the nineteenth century, although some important insights were gained during classical times. Aristotle (384–322 bc) noted that the ratio of brain size to body size was greatest in more intellectually advanced species, such as humans. Unfortunately, he made the error of claiming that cognition was a product of  4 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE the heart rather than the brain. He believed that the brain acted as a coolant system: the higher the intellect, the larger the cooling system needed. In the Roman age, Galen (circa ad 129–199) observed brain injury in gladiators and noted that nerves project to and from the brain. Nonetheless, he believed that mental experiences themselves resided in the ventricles of the brain. This idea went essentially unchallenged for well over 1,500 years. For example, when Vesalius (1514–1564), the father of modern anatomy, published his plates of dissected brains, the ventricles were drawn in exacting detail, whereas the cortex was drawn crudely and schematically (see Figure 1.2). Others followed in this tradition, often drawing the surface of the brain like the intestines. This situation probably reflected a lack of interest in the cortex rather than a lack of penmanship. It is not until one looks at the drawings of Gall and Spurzheim (1810) that the features of the brain become recognizable to modern eyes. FIGURE 1.2: Drawings of the brain from Vesalius (1543) (top), de Viessens (1685) (bottom left) and Gall and Spurzheim (1810) (bottom right). Note how the earlier two drawings emphasized the ventricles and/or misrepresented the cortical surface.  Introducing cognitive neuroscience 5 Gall (1758–1828) and Spurzheim (1776–1832) received a bad press, KEY TERMS historically speaking, because of their invention and advocacy of phrenology. Phrenology had two key assumptions: first, that different regions of the brain Phrenology The failed idea that perform different functions and are associated with different behaviors; and individual differences in second, that the size of these regions produces distortions of the skull and cognition can be mapped correlates with individual differences in cognition and personality. Taking onto differences in skull these two ideas in turn, the notion of functional specialization within the shape. brain has effectively endured into modern cognitive neuroscience, having Functional specialization seen off a number of challenges over the years (Flourens, 1824; Lashley, Different regions of the 1929). The observations of Penfield and co-workers on the electrically brain are specialized for stimulated brain provide some striking examples of this principle. However, different functions. the functional specializations of phrenology were not based on controlled experiments and were not constrained by theories of cognition. For example, Fowler’s famous phrenologist’s head had regions dedicated to “parental love,” “destructiveness” and “firmness” (Figure 1.3). Moreover, skull shape has nothing to do with cognitive function. Although phrenology was fatally flawed, the basic idea of different FIGURE 1.3: The parts of the brain serving different functions paved the way for future phrenologist’s head was developments in the nineteenth century, the most notable of which are Broca’s used to represent the (1861) reports of two brain-damaged patients. Broca documented two cases hypothetical functions of different regions of the brain. in which acquired brain damage had impaired the ability to speak but left © Photos.com/Thinkstock other aspects of cognition relatively intact. He concluded that language could be localized to a particular region of the brain. Subsequent studies argued that language itself was not a single entity but could be further subdivided into speech recognition, speech production and conceptual knowledge (Lichtheim, 1885; Wernicke, 1874). This was motivated by the observation that brain damage can lead either to poor speech comprehension and good production, or good speech comprehension and poor production (see Chapter 12 for full details). This suggests that there are at least two speech faculties in the brain and that each can be independently impaired by brain damage. This body of work was a huge step forward in terms of thinking about mind and brain. First, empirical observations were being used to determine the building blocks of cognition (is language a single module?) rather than listing them from first principles. Second, and related, they were developing models of cognition that did not make direct reference to the brain. That is, one could infer that speech recognition and production were separable without necessarily knowing where in the brain they were located, or how the underlying neurons brought these processes  6 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE K EY TERMS about. The approach of using patients with acquired brain damage to inform theories of normal cognition is called cognitive neuropsychology and Cognitive remains influential today (Chapter 5 discusses the logic of this method in neuropsychology detail). Cognitive neuropsychology is now effectively subsumed within the The study of brain-­ damaged patients to term “cognitive neuroscience,” where the latter phrase is seen as being less inform theories of normal restrictive in terms of methodology. cognition. Whereas discoveries in the neurosciences continued apace throughout Information processing the nineteenth and twentieth centuries, the formation of psychology as a An approach in which discipline at the end of the nineteenth century took the study of the mind behavior is described in away from its biological underpinnings. This did not reflect a belief in terms of a sequence of dualism. It was due, in part, to some pragmatic constraints. Early pioneers cognitive stages. of psychology, such as William James and Sigmund Freud, were interested in topics like consciousness, attention and personality. Neuroscience has had virtually nothing to say about these issues until quite recently. Another reason for the schism between psychology and biology lies in the notion that one can develop coherent and testable theories of cognition that do not make claims about the brain. The modern foundations of cognitive psychology lie in the computer metaphor of the brain and the information-processing approach, popular from the 1950s onwards. For example, Broadbent (1958) argued that much of cognition consists of a sequence of processing stages. In his simple model, perceptual processes occur, followed by attentional processes that transfer information to short-term memory and thence to long-term memory (see also Atkinson & Shiffrin, 1968). These were often drawn as a series of box-and-arrow diagrams (e.g., Figure 1.4). The implication was that one could understand the cognitive system in the same way as one FIGURE 1.4: Examples of box-and-arrow and connectionist models of cognition. Both represent ways of describing cognitive processes that need not make direct reference to the brain.  Introducing cognitive neuroscience 7 could understand the series of steps performed by a computer program, and KEY TERMS without reference to the brain. The notion that the brain contains different regions of functional Modularity The notion that certain specialization has been around in various guises for 200 years. However, cognitive processes (or one particular variation on this theme has attracted particular attention regions of the brain) are and controversy—namely Fodor’s (1983, 1998) theory of modularity. restricted in the type of First, Fodor makes a distinction between two different classes of cognitive information they process. process: central systems and modules. The key difference between them Domain specificity relates to the types of information they can process. Modules are held to The idea that a cognitive demonstrate domain specificity in that they process only one particular process (or brain region) type of information (e.g., color, shape, words, faces), whereas central is dedicated solely to systems are held to be domain independent in that the type of information one particular type of processed is non-specific (candidates would be memory, attention, executive information (e.g., colors, faces, words). functions). According to Fodor, one advantage of modular systems is that, by processing only a limited type of information, they can operate rapidly, Interactivity efficiently and in isolation from other cognitive systems. An additional Later stages of processing can begin before earlier claim is that modules may be innately specified in the genetic code. Many stages are complete. of these ideas have been criticized on empirical and theoretical grounds. For example, it has been suggested that domain specificity is not innate, although Top-down processing The influence of later stag- the means of acquiring it could be (Karmiloff-Smith, 1992). Moreover, es on the processing of systems like reading appear modular in some respects but cannot be innate earlier ones (e.g., memory because they are recent in evolution. Others have argued that evidence for influences on perception). interactivity suggests that modules are not isolated from other cognitive Bottom-up processing processes (Farah, 1994). The passage of informa- The idea of the mind as a computer program has advanced over the tion from simpler (e.g., years along with advances in computational science. For example, many edges) to more complex cognitive models contain some element of interactivity and parallel (e.g., objects). processing. Interactivity refers to the fact that stages in processing may Parallel processing not be strictly separate and that later stages can begin before earlier Different information is stages are complete. Moreover, later stages can influence the outcome of processed at the same early ones (top-down processing, in contrast to bottom-up processing). time (i.e., in parallel). Parallel processing refers to the fact that lots of different information Neural network models can be processed simultaneously (by contrast, serial computers process Computational models each piece of information one at a time). Although these computationally in which information explicit models are more sophisticated than earlier box-and-arrow processing occurs using diagrams, they, like their predecessors, do not always make contact with many interconnected nodes. the neuroscience literature. COMPUTATIONAL AND CONNECTIONIST MODELS OF COGNITION In the 1980s, powerful computers became widely accessible as never before. This enabled cognitive psychologists to develop computationally explicit models of cognition (that literally calculate a set of outputs given a set of inputs) rather than the computationally inspired, but underspecified, box-and- arrow approach. One particular way of implementing computational models has been very influential; namely the neural network, connectionist or parallel distributed processing (PDP) approach (McClelland et al., 1986). These models are considered in a number of places throughout this book, notably in the chapters dealing with memory, speaking and literacy.  8 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE Connectionist models have a number of architectural features. First, they are composed of arrays of simple information-carrying units called nodes. Nodes are information-carrying in the sense that they respond to a particular set of inputs (e.g., certain letters, certain sounds) and produce a restricted set of outputs. The responsiveness of a node depends on how strongly it is connected to other nodes in the network (the “weight” of the connection) and how active the other nodes are. It is possible to calculate, mathematically, what the output of any node would be, given a set of input activations and a set of weights. There are a number of advantages to this type of model. For example, by adjusting the weights over time as a result of experience, the model can develop and learn. The parallel processing enables large amounts of data to be processed simultaneously. A more controversial claim is that they have “neural plausibility.” Nodes, activation and weights are in many ways analogous to neurons, firing rates and neural connectivity, respectively. However, these models have been criticized for being too powerful in that they can learn many things that real brains cannot (Pinker & Prince, 1988). A more moderate view is that connectionist models provide examples of ways in which the brain might implement a given cognitive function, and they generate new predictions that can then be tested. Whether or not the brain actually does implement cognition in that particular way will ultimately be a question for empirical research in cognitive neuroscience. K EY TERM The birth of cognitive neuroscience Nodes It was largely advances in imaging technology that provided the driving force The basic units of neural for modern-day cognitive neuroscience. Raichle (1998) describes how brain network models that are imaging was in a “state of indifference and obscurity in the neuroscience activated in response to community in the 1970s” and might never have reached prominence if it were activity in other parts of not for the involvement of cognitive psychologists in the 1980s. Cognitive the network. psychologists had already established experimental designs and information- processing models that could potentially fit well with these emerging methods. It is important to note that the technological advances in imaging not only led to the development of functional imaging, but also enabled brain lesions to be described precisely in ways that were never possible before (except at postmortem). Present-day cognitive neuroscience is composed of a broad diversity of methods. These will be discussed in detail in subsequent chapters. At this juncture, it is useful to compare and contrast some of the most prominent methods. The distinction between recording methods and stimulation methods is crucial in cognitive neuroscience. Direct electrical stimulation of the brain in humans is now rarely carried out as a research tool, although it has some therapeutic uses (e.g., in Parkinson’s disease). The modern-day equivalent of these studies uses stimulation across the skull rather than directly to the brain (i.e., transcranially). This includes transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES). These will be considered in Chapter 5, alongside the effect of organic brain lesions. Electrophysiological methods (EEG/ERP and single-cell recordings) and magnetophysiological methods (MEG) record the electrical and magnetic properties of neurons themselves. These methods are considered in Chapter 3. In contrast, functional imaging methods (PET, fMRI and fNIRS) record  Introducing cognitive neuroscience 9 4 Naturally MEG & ERP Functional MRI occurring 3 PET lesions Brain 2 Spatial resolution (log mm) Map 1 TMS Column 0 Multi-unit Layer –1 recording Neuron –2 Dendrite –3 Single-cell recording Synapse –4 –3 –2 –1 0 1 2 3 4 5 6 7 Millisecond Second Minute Hour Day Temporal resolution (log seconds) FIGURE 1.5: The methods of cognitive neuroscience can be categorized according to their spatial and temporal resolution. Adapted from Churchland and Sejnowski, 1988. physiological changes associated with blood supply to the brain, which evolve more slowly over time. These are called hemodynamic methods and are considered in Chapter 4. The methods of cognitive neuroscience can be placed on a number of dimensions (see Figure 1.5): KEY TERM The temporal resolution refers to the accuracy with which one can measure when an event is occurring. The effects of brain damage are Temporal resolution permanent and so this has no temporal resolution as such. Methods The accuracy with which one can measure when such as EEG, MEG, TMS and single-cell recording have millisecond an event (e.g., a physio- resolution. fMRI has a temporal resolution of several seconds that logical change) occurs. reflects the slower hemodynamic response. THE DIFFERENT METHODS USED IN COGNITIVE NEUROSCIENCE Method Method type Invasiveness Brain property used EEG/ERP Recording Noninvasive Electrical Single-cell (and Recording Invasive Electrical multi-unit) recordings TMS Stimulation Noninvasive Electromagnetic tES Stimulation Noninvasive Electrical MEG Recording Noninvasive Magnetic PET Recording Invasive Hemodynamic fMRI Recording Noninvasive Hemodynamic fNIRS Recording Noninvasive Hemodynamic  10 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE K EY TERM The spatial resolution refers to the accuracy with which one can measure where an event is occurring. Lesion and functional imaging methods Spatial resolution have comparable resolution at the millimeter level, whereas single-cell The accuracy with recordings have spatial resolution at the level of the neuron. which one can measure where an event (e.g., a The invasiveness of a method refers to whether the equipment is located physiological change) is internally or externally. PET is invasive because it requires an injection of occurring. a radio-labeled isotope. Single-cell recordings are performed on the brain itself and are normally only carried out in non-human animals. D O ES C O G N I T IVE PSYCHOLOGY NE E D THE BRAIN? As already noted, cognitive psychology developed substantially from the 1950s, using information-processing models that do not make direct reference to the brain. If this way of doing things remains successful, then why change? Of course, there is no reason why it should change. The claim is not that cognitive neuroscience is replacing cognitive psychology (although some might endorse this view), but merely that cognitive psychological theories can inform theories and experiments in the neurosciences and vice versa. However, others have argued that this is not possible by virtue of the fact that information-processing models do not make claims about the brain (Coltheart, 2004b; Harley, 2004). Coltheart (2004b) poses the question: Has cognitive neuroscience, or if not might it ever (in principle, or even in practice), successfully used data from cognitive neuroimaging FIGURE 1.6: One could take many different measures in to make theoretical decisions entirely at the cognitive level (e.g. to a forced-choice response adjudicate between competing information-processing models of some task: behavioral (reaction cognitive system)? time [RT], errors, eye- (p. 21) movements) or biological (electromyographic [EMG], Henson (2005) argues that it can in principle and that it does in practice. He BOLD response in fMRI or argues that data from functional imaging (blood flow, blood oxygen) comprise electrical activity in EEG). All measures could potentially just another dependent variable that one can measure. For example, there are a be used to inform cognitive number of things that one could measure in a standard forced-choice reaction- theory. time task: reaction time, error rates, sweating (skin conductance response), Adapted from Henson, 2005. muscle contraction (electromyograph), scalp electrical recordings (EEG) or By kind permission of the hemodynamic changes in the brain (fMRI)—see Figure 1.6. Each measure Experimental Psychology Society. will relate to the task in some way and can be used to inform theories about the task. Eye-movements EEG To illustrate this point, consider an example. One could ask a simple question RT such as: Does visual recognition of words and letters involve computing a representation fMRI that is independent of case? For example, does the reading system treat “E” and “e” as equivalent at an early stage in processing or are “E” and “e” treated as different letters until EMG some later stage (e.g., saying them aloud)? A way of investigating this using a reaction-time  Introducing cognitive neuroscience 11 measure is to present the same word twice in the same case (e.g., RADIO- RADIO) or different case (e.g., radio-RADIO) and compare this with situations in which the word differs (e.g., mouse-RADIO, MOUSE-RADIO). One general finding in reaction-time studies is that it is faster to process a stimulus if the same stimulus has recently been presented. For example, if asked to make a speeded decision about RADIO (e.g., is it animate or inanimate?), performance will be faster if it has been previously encountered. Dehaene et al. (2001) investigated this mechanism by comparing reaction-time measures with functional imaging (fMRI) measures. In this task, the first word in each pair was presented very briefly and was followed by visual noise. This prevented the participants from consciously perceiving it and, hence, one can be sure that they are not saying the word. The second word was consciously seen and requires a response. Dehaene et al. found that reaction times were FIGURE 1.7: Both reaction faster to the second word when it follows the same word, irrespective of case. times and fMRI activation Importantly, there was a region in the left fusiform cortex that shows the in the left fusiform region same effect (although in terms of “activation” rather than response time). demonstrate more efficient This is shown in Figure 1.7. In this concrete example, it is meaningless to processing of words if they are preceded by subliminal argue that one type of measure is “better” for informing cognitive theory presentation of the same (to return to Coltheart’s question) given that both are measuring different word, irrespective of case. aspects of the same event. One could explore the nature of this effect further Adapted from Dehaene et al., by, for instance, presenting the same word in different languages (in bilingual 2001. 12 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE speakers), presenting the words in different locations on the screen and so on. This would provide further insights into the nature of this mechanism (e.g., what aspects of vision does it entail? Does it depend on word meaning?). However, both reaction-time measures and brain-based measures could be potentially informative. It is not the case that functional imaging is merely telling us where cognition is happening and not how it is happening. Another distinction that has been used to contrast cognitive psychology and cognitive neuroscience is that between software and hardware, respectively (Coltheart, 2004b; Harley, 2004). This derives from the familiar computer analogy in which one can, supposedly, learn about information processing (software) without knowing about the brain (hardware). As has been shown, to some extent this is true. But the computer analogy is a little misleading. Computer software is written by computer programmers (who, incidentally, have human brains). However, information processing is not written by some third person and then inscribed into the brain. Rather, the brain provides causal constraints on the nature of information processing. This is not analogous to the computer domain in which the link between software and hardware is arbitrarily determined by a computer programmer. To give a simple example, one model of visual word recognition suggests that words are recognized by searching words in a mental dictionary one by one until a match is found (Forster, 1976). The weight of evidence from cognitive psychology argues against this serial search, and in favor of words being searched in parallel (i.e., all candidate words are considered at the same time). But why does human cognition work like this? Computer programs can be made to recognize words adequately with both serial search and parallel search. The reason why human information processing uses a parallel search and not a serial search probably lies in the relatively slow neural response time (acting against serial search). This constraint does not apply to the fast processing of computers. Thus, cognitive psychology may be sufficient to tell us the structure of information processing but it may not answer deeper questions about why information processing should be configured in that particular way. The biological constraints imposed by the brain shape the nature and limitations of cognition. D O ES N EU RO S CIE NCE NE E D COGNITIVE PS YC H O LO G Y ? It would be no exaggeration to say that the advent of techniques such as functional imaging has revolutionized the brain sciences. For example, consider some of the newspaper headlines that have appeared over the years (Figure 1.8). Of course, it has been well known since the nineteenth century that pain, mood, intelligence and sexual desire are largely products of processes in the brain. The reason headlines such as these are extraordinary is because now the technology exists to be able to study these processes in vivo. Of course, when one looks inside the brain one does not “see” memories, thoughts, perceptions and so on (i.e., the stuff of cognitive psychology). Instead, what one sees is gray matter, white matter, blood vessels and so on (i.e., the stuff of neuroscience). It is the latter, not the former, that one observes when conducting a functional imaging experiment. Developing a  Introducing cognitive neuroscience 13 FIGURE 1.8: The media framework for linking the two will necessarily entail dealing with the mind– loves to simplify the findings body problem either tacitly or explicitly. This is a daunting challenge. of cognitive neuroscience. Many newspaper stories Is functional imaging going to lead to a more sophisticated understanding appear to regard it as of the mind and brain than was achieved by the phrenologists? Some of counterintuitive that sex, the newspaper reports in Figure 1.8 suggest it might not. One reason why pain and mood would be phrenology failed is because the method had no real scientific grounding; the products of the brain. same cannot be said of functional imaging. Another reason why phrenology Sunday Times, 21 November failed was that the psychological concepts used were naïve. It is for this reason 1999; Metro, 5 January 2001; The Observer, 12 March 2000. that functional imaging and other advances in neuroscience do require the insights from cognitive psychology to frame appropriate research questions and avoid becoming a new phrenology (Uttal, 2001). The question of whether cognitive, mind-based concepts will eventually become redundant (under a reductionist account) or coexist with neural- based accounts (e.g., as in dual-aspect theory) is for the future to decide. But for now, cognitive, mind-based concepts have an essential role to play in cognitive neuroscience. F RO M M O D ULES T O N ET WO R KS What does the future of cognitive neuroscience look like? Although nobody knows for sure, much current research is centered on understanding the mind and brain as a network. A network is a dynamically changing pattern of activity over several brain regions. Rather than thinking of the brain as a single network, there might be a multitude of different networks which are, themselves, switched on or off depending on the kind of thought or behavior KEY TERM that is needed. Thus, not only do brain regions have a degree of functional Connectome specialization, but entire networks may also have some specializations. A comprehensive map This network approach is exemplified by current efforts to map the human of neural connections in the brain that may be connectome (Sporns, 2011). The Human Connectome Project was launched thought of as its “wiring in 2010 at a cost of over $40M. The aim is to try to map out the pattern diagram.” of connectivity in the human brain at a macro, i.e., millimeter, scale (rather  14 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE than the micro level of individual synapses). The project is based on MRI techniques that measure structural connectivity (essentially white matter fibers) and functional connectivity (essentially correlated patterns of brain activity between regions). By scanning and testing thousands of people it will ONLINE RESOURCES be possible to identify differences in the connectome that are linked to disease Delve deeper and also, of particular relevance here, to understand how these networks into the Human support cognitive function. This can be done by, for instance, linking Connectome Project individual differences in the connectome to individual differences in specific (humanconnectome. cognitive abilities (Barch et al., 2013). Thus, it is not just an enterprise for org) and watch TEDx talks on connectomics biologists and neuroimagers—it also requires the input of psychologists who by Jeff Lichtman and understand cognition. A complementary approach is to map the connectome David van Essen. Visit at the micro scale of individual synapses. This is a daunting prospect as there the companion website are 1010 neurons linked by 1014 synaptic connections (Azevedo et al., 2009). at www.routledge. By comparison, the size of a human genome is far smaller (3×109). Aside com/cw/ward. from the sheer scale of this challenge, there is no obvious way of interpreting the connectome “code” (unlike the genome where there is a simple mapping between the code and the proteins they create). K EY TERM Of course, networks are nothing new. Networks were there from the start Graph theory in the form of black-box-and-arrow diagrams. However, the contemporary A mathematical tech- and emerging landscape looks very different from this. Firstly, the network nique for computing the architecture that supports cognition is derived from biologically based pattern of connectivity (or observations of the structural and functional connectome. This is supported “wiring diagram”) from a by advanced mathematical tools such as graph theory (Bullmore & Sporns, set of correlations. 2009). This essentially creates a wiring diagram, rather like a subway map, in which some brain regions act as central hubs within the network (where several subway lines cross, in that analogy) and other regions are less connected (the suburbs, in that analogy). Secondly, there has been a shift away from conceptualizing the hubs in the network as highly specialized units. Instead, brain regions might perform a range of different functions depending on which other parts of the brain they are communicating with. A good example is Broca’s region itself which, whilst everyone agrees it is important for language, seems to also be involved in other cognitive processes such as detecting musical violations (Koelsch et al., 2006). Does this mean that the era of functional specialization, stretching from phrenology through to Broca and Penfield, is now over? This is certainly not the case. It has even been argued on first principles that if the brain is a network then the different hubs in the network must have different functional specializations (Sporns & Betzel, 2016), except in the hypothetical scenario that all regions in the network connect equally strongly to each other (in which case each hub is identical). However, the function assigned to a region may be harder to map onto simple cognitive concepts in this new framework. For instance, the function of a brain region may be something like “integrating vision and speech” rather than “a store of words.” Thus, the central challenge for cognitive neuroscience for the future is to develop new ways of describing the relationship between brain structure (notably connectomics) and function (i.e., cognition and behavior). Barrett and Satpute (2013) offer a useful summary of three different approaches as shown in Figure 1.9. In the first scenario (a), there is a very simple one-to-one mapping between different brain regions and different cognitive functions.  Introducing cognitive neuroscience 15 FIGURE 1.9: Three different ways in which different brain structures might be mapped to different functions (tasks and processes). In (a) there is a one-to-one association between brain structure and function whereas in both (b) and (c) a network of regions may make different contributions to a given function. In (b) the network consists of specialized units that interact, but in (c) the network consists of interactions between nonspecialized units. From Barrett and Satpute (2013).  16 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE Few researchers would endorse such a view. In the second scenario (b), there is still a high degree of specialization of brain regions but multiple regions need to interact to generate a cognitive function. In the third scenario (c) there is far less specialization of regions and cognitive functions are generated by the interaction of multiple networks (with each network having some specialization). Barrett and Satpute (2013) favor this third option, although others argue that the cognitive architecture of the brain is more like the second option (Vytal & Hamann, 2010). SUMMARY AND KEY POINTS OF THE CHAPTER The mind–body problem refers to the question of how physical matter (the brain) can produce mental experiences, and this remains an enduring issue in cognitive neuroscience. To some extent, the different regions of the brain are specialized for different functions. Functional neuroimaging has provided the driving force for much of the development of cognitive neuroscience, but there is a danger in merely using these methods to localize cognitive functions without understanding how they work. Cognitive psychology has developed as a discipline without ONLINE RESOURCES making explicit references to the brain. However, biological measures can provide an alternative source of evidence to inform Visit the companion cognitive theory and the brain must provide constraining factors website at www. on the nature and development of the information-processing routledge.com/cw/ward for: models of cognitive science. Attempting to map the human connectome, and link it to References to key papers and readings cognition, is the greatest challenge for the next generation of Video interviews cognitive neuroscientists. Although old concepts will remain (e.g., on key topics the idea of functional specialization), they may be understood in with leading entirely new ways. neuroscientists Wilder Penfield and Michael Gazzaniga, and philosopher Ned EXAMPLE ESSAY QUESTIONS Block Multiple-choice questions and What is the “mind–body problem” and what frameworks have interactive flashcards been put forward to solve it? to test your Is cognitive neuroscience the new phrenology? knowledge Does cognitive psychology need the brain? Does neuroscience Downloadable need cognitive psychology? glossary  Introducing cognitive neuroscience 17 RECOMMENDED FURTHER READING Henson, R. (2005). What can functional neuroimaging tell the experimental psychologist? Quarterly Journal of Experimental Psychology, 58A, 193–233. An excellent summary of the role of functional imaging in psychology and a rebuttal of common criticisms. This debate can also be followed in a series of articles in Cortex (2006, 42, 387–427). Shallice, T., & Cooper, R. P. (2011). The organisation of mind. Oxford, UK: Oxford University Press. The chapters on “conceptual foundations” deal with many of the issues touched on in the present chapter in more detail. Uttal, W. R. (2001). The new phrenology: The limits of localizing cognitive processes in the brain. Cambridge, MA: MIT Press. An interesting overview of the methods and limitations of cognitive neuroscience. Wickens, A. P. (2015). A history of the brain: How we have come to understand the most complex object in the universe. New York: Psychology Press. A good place to start for the history of neuroscience. CH A P TE R 2 Introducing the brain CONTENTS Structure and function of the neuron 19 The gross organization of the brain 24 The cerebral cortex 28 The subcortex 30 The midbrain and hindbrain 32 Summary and key points of the chapter 33 Example essay questions 33 Recommended further reading 34 It is hard to begin a chapter about the brain without waxing lyrical. The brain is the physical organ that makes all our mental life possible. It enables us to read these words, and to consider thoughts that we have never considered before—or even to create thoughts that no human has considered before. This book will scratch the surface of how this is all possible, but the purpose of this chapter is more mundane. It offers a basic guide to the structure of the brain, starting from a description of neurons and working up to a description of how these are organized into different neuroanatomical systems. The emphasis is on the human brain rather than the brain of other species. S T R U C T U R E AN D F U N C T I O N O F THE NE URON All neurons have basically the same structure. They consist of three components: a cell body (or soma), dendrites and an axon, as shown in Figure 2.1. Although neurons have the same basic structure and function, it is important to note that there are some significant differences between different types of neurons in terms of the spatial arrangements of the dendrites and axon.  20 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE FIGURE 2.1: Neurons consist of three basic features: a cell body, dendrites that receive information and axons that send information. In this diagram the axon is myelinated to speed the conduction time. KEY TERMS Neuron A type of cell that makes up the nervous system and supports, among other things, cognitive function. Cell body The cell body contains the nucleus and other organelles. The nucleus Part of the neuron con- contains the genetic code, and this is involved in protein synthesis. Proteins taining the nucleus and serve a wide variety of functions from providing scaffolding to chemical other organelles. signaling (they can act as neurotransmitters and receptors in neurons). Dendrites Neurons receive information from other neurons and they make a “decision” Branching structures that about this information (by changing their own activity) that can then be passed carry information from on to other neurons. From the cell body, a number of branching structures other neurons. called dendrites enable communication with other neurons. Dendrites receive Axon information from other neurons in close proximity. The number and structure A branching structure of the dendritic branches can vary significantly depending on the type of that carries information neuron (i.e., where it is to be found in the brain). The axon, by contrast, sends to other neurons and information to other neurons. Each neuron consists of many dendrites but transmits an action potential. only a single axon (although the axon may be divided into several branches called collaterals). TEN INTERESTING FACTS ABOUT THE HUMAN BRAIN (1) There are 86 billion neurons in the human brain (Azevedo et al., 2009). (2) Each neuron connects with around 10,000 other neurons. As such, there are over 3,000 times as many synapses in one person’s brain than there are stars in our whole galaxy. (3) If each neuron connected with every single other neuron, our brain would be 12.5 miles in diam- eter (Nelson & Bower, 1990). This is the length of Manhattan Island. This leads to an important conclusion—namely, that neurons only connect with a small subset of other neurons. Neurons tend to communicate only with their neighbors in what has been termed a “small-world” archi- tecture (Sporns & Zwi, 2004). Long-range connections are the exception rather than the rule. (4) The idea that we only use 10 percent of the cells in our brain is generally considered a myth (Beyerstein, 1999). It used to be thought that only around 10 percent of the cells in the brain were neurons (the rest being cells called glia), hence a plausible origin for the myth. This “fact” also turns out to be inaccurate, with the true ratio of neurons to glia being closer to 1:1 (Azevedo et al., 2009). Glia serve a number of essential support functions; for example, they are involved in tissue repair and in the formation of myelin.  Introducing the brain 21 (5) The brain makes up only 2 percent of body weight. (6) It is no longer believed that neurons in the brain are incapable of being regenerated. It was once widely believed that we are born with our full complement of neurons and that new neurons are not generated. This idea is now untenable, at least in a region called the dentate gyrus (for a review, see Gross, 2000). (7) On average, we lose a net amount of one cortical neuron per second. A study has shown that around 10 percent of our cortical neurons perish between the ages of 20 and 90 years— equivalent to 85,000 neurons per day (Pakkenberg & Gundersen, 1997). (8) Identical twins do not have anatomically identical brains. A comparison of identical and nonidentical twins suggests that the three-dimensional cortical gyral pattern is determined primarily by non-genetic factors, although brain size is strongly heritable (Bartley et al., 1997). (9) People with autism have larger brains in early life (Abell et al., 1999). They also have large heads to accommodate them. There is unlikely to be a simple relationship between brain size and intellect (most people with autism have low IQ), and brain efficiency may be unrelated to size. (10) Men have larger brains than women, but the female brain is more folded, implying an increase in surface area that may offset any size difference (Luders et al., 2004). The total number of cortical neurons is related to gender, but not overall height or weight (Pakkenberg & Gundersen, 1997). The terminal of an axon flattens out into a disc-shaped structure. It KEY TERMS is here that chemical signals enable communication between neurons via a small gap termed a synapse. The two neurons forming the synapse are Synapse The small gap between referred to as presynaptic (before the synapse) and postsynaptic (after the neurons in which synapse), reflecting the direction of information flow (from axon to dendrite). neurotransmitters are When a presynaptic neuron is active, an electrical current (termed an released, permitting action potential) is propagated down the length of the axon. When the action signaling between potential reaches the axon terminal, chemicals are released into the synaptic neurons. cleft. These chemicals are termed neurotransmitters. (Note that a small Action potential proportion of synapses, such as retinal gap junctions, signal electrically and A sudden change not chemically.) Neurotransmitters bind to receptors on the dendrites or cell (depolarization and body of the postsynaptic neuron and create a synaptic potential. The synaptic repolarization) in the potential is conducted passively (i.e., without creating an action potential) electrical properties of the neuron membrane in through the dendrites and soma of the postsynaptic neuron. These passive an axon, which forms the currents form the basis of EEG. These different passive currents are summed basis for how neurons together and if their summed activity exceeds a certain threshold when they code information (in reach the beginning of the axon in the postsynaptic neuron, then an action the form of the rate potential (an active electrical current) will be triggered in this neuron. In this and synchrony of action way, different neurons can be said to be “communicating” with each other. potentials). This is shown in Figure 2.2. It is important to note that each postsynaptic Neurotransmitters neuron sums together many synaptic potentials, which are generated at many Chemical signals that are different and distant dendritic sites (in contrast to a simple chain reaction released by one neuron between one neuron and the next). Passive conduction tends to be short range and affect the properties of other neurons. because the electrical signal is impeded by the resistance of the surrounding matter. Active conduction enables long-range signaling between neurons by the propagation of action potentials.  22 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE FIGURE 2.2: Electrical currents are actively transmitted through axons by an action potential. Electrical currents flow passively through dendrites and soma of neurons, but will initiate an action potential if their summed potential is strong enough at the start of the axon (called the hillock). Electrical signaling and the action potential Each neuron is surrounded by a cell membrane that acts as a barrier to the passage of certain chemicals. Within the membrane, certain protein molecules act as gatekeepers and allow particular chemicals in and out under certain conditions. These chemicals consist, among others, of charged sodium (Na+) and potassium (K+) ions. The balance between these ions on the inside and outside of the membrane is such that there is normally a resting potential of −70 mV across the membrane (the inside being negative relative to the outside). Voltage-gated ion channels are of particular importance in the generation of an action potential. They are found only in axons, which is why only the axon is capable of producing action potentials. The sequence of events is as follows (see also Figure 2.3): 1. If a passive current of sufficient strength flows across the axon membrane, this begins to open the voltage-gated Na+ channels. 2. When the channel is opened, then Na+ may enter the cell and the negative potential normally found on the inside is reduced (the cell is said to depolarize). At about −50 mV, the cell membrane becomes completely permeable and the charge on the inside of the cell momentarily reverses. This sudden depolarization and subsequent repolarization in electrical charge across the membrane is the action potential. 3. The negative potential of the cell is restored via the outward flow of K+ through voltage-gated K+ channels and closing of the voltage-gated Na+ channels. 4. There is a brief period in which hyperpolarization occurs (the inside is more negative than at rest). This makes it more difficult for the axon to depolarize straight away and prevents the action potential from traveling backwards.  Introducing the brain 23 FIGURE 2.3: The action potential consists of a number of phases. An action potential in one part of the axon opens adjacent voltage- sensitive Na+ channels, and so the action potential moves progressively down the length of the axon, starting from the cell body and ending at the axon terminal. The conduction of the action potential along the axon may KEY TERM be speeded up if the axon is myelinated. Myelin is a fatty substance that is deposited around the axon of some cells (especially those that carry motor Myelin signals). It blocks the normal Na+/K+ transfer and so the action potential A fatty substance that is deposited around the jumps, via passive conduction, down the length of the axon at the points at axon of some neurons which the myelin is absent (called nodes of Ranvier). Destruction of myelin is that speeds conduction. found in a number of pathologies, notably multiple sclerosis. Chemical signaling and the postsynaptic neuron When the action potential reaches the axon terminal, the electrical signal initiates a sequence of events leading to the release of neurotransmitters into the synaptic cleft. Protein receptors in the membrane of the postsynaptic neurons bind to the neurotransmitters. Many of the receptors are transmitter- gated ion channels (not to be confused with voltage-gated ion channels found in the axon). This sets up a localized flow of charged Na+, K+ or chloride (Cl–), which creates the synaptic potential. Some neurotransmitters (e.g., GABA) have an inhibitory effect on the postsynaptic neuron (i.e., by making it less likely to fire). This can be achieved by making the inside of the neuron more negative than normal and hence harder to depolarize (e.g., by opening transmitter-gated Cl– channels). Other neurotransmitters (e.g., glutamate) have excitatory effects on the postsynaptic neuron (i.e., by making it more likely to fire). These synaptic potentials are then passively conducted as already described. Glutamate and GABA are the workhorse neurotransmitters of the brain in that nearly every neuron produces one or other of these. Note that it is not the chemicals themselves that make them excitatory and inhibitory. Rather it is the effect that they have on ion channels in the  24 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE membrane which either pump positive or negative ions, thus making an action potential more or less likely. Other common neurotransmitters are serotonin, dopamine, acetylcholine and noradrenaline. These are often considered to have modulatory functions. Rather than being distributed ONLINE RESOURCE throughout the brain, as is the case with GABA and glutamate, the Do you need to get cell bodies of the neurons that release these neurotransmitters tend to up to speed on your be localized to specific brain areas, but their axonal projections spread neuroscience basics? diffusely throughout the brain. Take a look at the companion website (www.routledge. How do neurons code information? com/cw/ward) for links to a YouTube The amplitude of an action potential does not vary, but the number of neuroscience crash action potentials propagated per second varies along a continuum. This rate course and a free of responding (also called the “spiking rate”) relates to the informational online Fundamentals of Neuroscience “code” carried by that neuron. For example, some neurons may have a high module from Harvard spiking rate in some situations (e.g., during speech), but not others (e.g., University. during vision), whereas other neurons would have a complementary profile. Neurons responding to similar types of information tend to be grouped together. This gives rise to the functional specialization of brain regions that was introduced in Chapter 1. If information is carried in the response rate of a neuron, what determines the type of information that the neuron responds to? The type of information that a neuron carries is related to the input it receives and the output it sends to other neurons. For example, the reason neurons in the primary auditory cortex can be considered to carry information about sound is because they receive input from a pathway originating in the cochlea and they send information to other neurons involved in more advanced stages of auditory processing (e.g., speech perception). However, imagine that one were to rewire the brain such that the primary auditory cortex was to receive inputs from the retinal pathway, originating in the eyes, rather than the auditory pathway (Sur & Leamey, 2001). In this case, the function of the primary “auditory” cortex would have changed (as would the type of information it carries) even though the region itself was not directly modified (only the inputs to it were modified). This general point is worth bearing in mind when one considers K EY TERMS what the function of a given region is. The function of a region is determined Gray matter by its inputs and outputs. As such, the extent to which a function can be Matter consisting primari- strictly localized is a moot point. ly of neuronal cell bodies. White matter T H E G RO S S O RGANIZATION OF THE BRAIN Tissue of the nervous system consisting primar- ily of axons and support Gray matter, white matter and cerebrospinal fluid cells. Neurons are organized within the brain to form white matter and gray matter. Glia Gray matter consists of neuronal cell bodies. White matter consists of axons Support cells of the and support cells (glia). The brain consists of a highly convoluted folded nervous system involved sheet of gray matter (the cerebral cortex), beneath which lies the white matter. in tissue repair and in In the center of the brain, beneath the bulk of the white matter fibers, lies the formation of myelin (among other functions). another collection of gray matter structures (the subcortex), which includes the basal ganglia, the limbic system and the diencephalon. Introducing the brain 25 FIGURE 2.4: There are three different kinds of white matter tract, depending on the nature of the regions that are connected. Adapted from Diamond et al., 1986. © 1986 by Coloring Concepts, Inc. Reprinted by permission of HarperCollins Publishers. FIGURE 2.5: The brain consists of four ventricles filled with cerebrospinal fluid (CSF): the lateral ventricles are found in each hemisphere, the third ventricle lies centrally around the subcortical structures and the fourth ventricle lies in the brainstem (hindbrain).  26 THE STUDENT’S GUIDE TO COGNITIVE NEUROSCIENCE K EY TERMS White matter tracts may project between different cortical regions within the same hemisphere (called association tracts), or project between different Corpus callosum cortical regions in different hemispheres (called commissures; the most A large white matter tract important commissure being the corpus callosum) or may project between that connects the two hemispheres. cortical and subcortical structures (called projection tracts)—see Figure 2.4. The brain also contains a number of hollow chambers termed ventricles, Ventricles shown in Figure 2.5. These were incorrectly revered for 1,500 years as being The hollow chambers of the brain that contain the seat of mental life. The ventricles are filled with cerebrospinal fluid (CSF), cerebrospinal fluid. which does serve some useful functions, albeit non-cognitive. The CSF carries waste metabolites, transfers some messenger signals and provides a protective Anterior Toward the front. cushion for the brain. Posterior Toward the back. A hierarchical view of the central nervous system Superior Brain evolution can be thought of as adding additional structures onto older Toward the top. ones, rather than replacing older structures with newer ones. For example, the Inferior main visual pathway in humans travels from the retina to the occipital lobe, Toward the bottom. but a number of older visual pathways also exist and contribute to vision (see Dorsal Chapter 7). These older pathways constitute the dominant form of seeing Toward the top. for other species such as birds and reptiles. Figure 2.6 illustrates the major Ventral structures of the brain, showing a hierarchical arrangement (older structures Toward the bottom. toward the bottom of the diagram). Lateral The outer part (cf. medial). Terms of reference and section Medial There are conventional directions for navigating around the brain, just as In or toward the middle. there is a north, south, east and west for navigating around maps. Anterior and posterior refer to directions toward the front and back of the brain, respectively. These are also called rostral and caudal, respectively, particularly in other species that have a tail (caudal refers to the tail end). Directions toward the top and bottom are referred to as superior and inferior, respectively;