Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain

Book Description

The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena.

The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.

Customer Reviews:

Great for Grads/Professional--confusing and convoluted for undergrad.......2006-11-17

I am currently taking a honors psych class which utilizes this textbook as a lab handout (we solve the exercises closing out each chapter). I find this book very hard to read due to the language and the explanations the authors use to explain certain topics. The book reads more like a guide for those already familiar with the subject matter, and the questions closing out each chapter are even harder to understand than the chapter text itself. If the authors wish the book to be of any help to undergrads who are not already familiar with the topic they should take a step back and revise the text so that it is understandable for all. NOTE TO UA STUDENTS THINKING OF TAKING THE CLASS WHICH UTILIZES THIS BOOK
---->dont.

Best introduction to neural network models of cognitive processes.......2006-03-23

"Computational Explorations in Cognitive Neuroscience" provides a very readable overview of state-of-the-art neural network models for human cognition with an emphasis on both biological plausibility and experimental (psychological/cognitive) evidence.

A new paradigm.......2000-09-27

In this book, research themes, which include perception, memory, language as well as high-level cognition, are explained in terms of computation. Their theory is based on brain science, computer science, and psychology. Though the authors speculate about the functions of each part of the brain and the relation among them to some extent, the authors propose a new paradigm to existing sciences. Their integrative approach and method are very simulative, and I've got a lot of hints from this book. But I don't need the usageof particular software, PDP++ in such a theoretical book. The authors explain and demonstrate their models and theories using PDP++ at the end of each chapter. If you want to study how to use PDP++ as well as their theories, this book will be extremely good one.

A new paradigm.......2000-09-27

In this book, research themes including perception, memory, and language as well as high-level cognition are explained in terms of computation. Their theories are based on brain science, computer science, and psychology. Though the authors speculate about the functions of the brain and the relation among them to some extent, the authors propose a new paradigm to existing sciences. Their integrative approach and method are very simulative, and I've got a lot of hints from this book. But I don't need the usage of particular software, PDP++ in such a theoretical book. The authors explain and demonstrate their models and theories using PDP++ at the end of each chapter. If you want to study how to use PDP++ as well as their theories, this book will be truly excellent.

Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)

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Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)

Manufacturer: The MIT Press
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Binding: Hardcover

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ASIN: 026204238X

Book Description

A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering experimental data. Bayesian Brain brings together contributions from both experimental and theoretical neuroscientists that examine the brain mechanisms of perception, decision making, and motor control according to the concepts of Bayesian estimation.

After an overview of the mathematical concepts, including Bayes' theorem, that are basic to understanding the approaches discussed, contributors discuss how Bayesian concepts can be used for interpretation of such neurobiological data as neural spikes and functional brain imaging. Next, contributors examine the modeling of sensory processing, including the neural coding of information about the outside world. Finally, contributors explore dynamic processes for proper behaviors, including the mathematics of the speed and accuracy of perceptual decisions and neural models of belief propagation.

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Brain Dynamics
Hermann Haken
Manufacturer: Springer-Verlag New York, Inc
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Binding: Hardcover

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ASIN: 3540430768

Book Description

(preliminary) Brain Dynamics is an introduction for graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences.
The approach in this book is through pulsed-coupled neural networks, with at their core the lighthouse and integrate-and-fire models, which allow for the highly flexible modelling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. As a more advanced topic, pulse-averaged equations and their application to movement coordination are discussed. The book closes with a short analysis of models versus the real neurophysiological system. The second edition has been thoroughly updated and augmented by an extensive chapter that discusses the interplay between pattern recognition and synchronization. Further, to enhance the usefulness as textbook and for self-study, the detailed solutions of all XX exercises throughout the text have been added.

Fast Oscillations in Cortical Circuits (Computational Neuroscience)

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Fast Oscillations in Cortical Circuits (Computational Neuroscience)
Roger D. Traub , John G. R. Jefferys , and Miles A. Whittington
Manufacturer: The MIT Press
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Binding: Hardcover

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ASIN: 0262201186

Book Description

The study of cortical oscillations is of great interest to those working in many areas of neuroscience. A fast coherent EEG rhythm called gamma or "40 Hz" has been implicated in cognition, as it may play a role in binding together features of objects. This rhythm may also be important for consciousness, as a number of drugs that induce general anesthesia disrupt the synchronization of the rhythm at clinically relevant concentrations. There is also suggestive evidence implicating dysfunction of gamma rhythms in Alzheimer's disease, and perhaps in other neuropsychiatric disorders.

In Fast Oscillations in Cortical Circuits, the authors use a combination of electrophysiological and computer modeling techniques to analyze how large networks of neurons can produce both epileptic seizures and functionally relevant synchronized oscillations. Specific topics covered include single hippocampal pyramid cells, hippocampal interneurons, synaptic interactions, gamma oscillations in brain slices as well as in vivo, the mechanisms of oscillation-synchronization (both local and long-range), the switch from gamma to beta frequencies and its implications for memory, and the significance of gamma oscillations for brain function.

The Computational Brain (Computational Neuroscience)

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A source of stimulation and frustration
Excellent
a great book
Good summary of empirical and experimental neuroscience

The Computational Brain (Computational Neuroscience)
Patricia Churchland , and Terrence J. Sejnowski
Manufacturer: The MIT Press
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Binding: Hardcover

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ASIN: 0262031884

Book Description

How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by The Computational Brain. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework.

Computer models constrained by neurobiological data can help reveal how -networks of neurons subserve perception and behavior - bow their physical interactions can yield global results in perception and behavior, and how their physical properties are used to code information and compute solutions. The Computational Brain focuses mainly on three domains: visual perception, learning and memory, and sensorimotor integration. Examples of recent computer models in these domains are discussed in detail, highlighting strengths and weaknesses, and extracting principles applicable to other domains. Churchland and Sejnowski show how both abstract models and neurobiologically realistic models can have useful roles in computational neuroscience, and they predict the coevolution of models and experiments at many levels of organization, from the neuron to the system.

The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques.

Patricia S. Churchland is Professor of Philosophy at the University of California, San Diego, Adjunct Professor at the Salk Institute, and a MacArthur Fellow. Terrence J. Sejnowski is Professor of Biology at the University of California, San Diego, Professor at the Salk Institute, where he is Director of the Computational Neurobiology Laboratory, and an Investigator of the Howard Hughes Medical Institute.

Customer Reviews:

A source of stimulation and frustration.......2007-02-14

There is an argument that this is a book of its time. It is nearly fifteen years since it was put together and a great deal of neural water has flowed under the bridge. The thematic enthusiasm for computationalism that dominates the book has not been convincingly proved in the meantime. If anything, the computational properties of models have been shown to entertain many unpleasant complexity results. Moreover, the localisation of brain functions grounded in naive interpretations of lesion effects has come under greater scrutiny due to detailed MRI results. Given twhat was known at the time, it is unsurprising that the book focuses on the visual system - a focus also found in Christof Koch's recent book. Acknowleding all that and more, it would be hard to find a better condensation of science, computationalism, and philosophical speculation than in this book.

Leaving aside downsides arising from recent discoveries that the authors could not have anticipated, the book can be frustrating to read at times. In particular, there is a tendency to introduce technical concepts and descriptors into accounts without prior definition. For example, very early on in a brief account of monkey vision there is mention of V4, MT, etc. The terms are neither defined nor explained. Strangely, in the introduction to networks, the inner product of two vectors is explained while the outer product is not. Small points but the oversight recurs.

The philosophical content in the book is light, but the assumptions driving the work are among the most contentious. There is no point reaming off a list but the book does not shirk supporing the brain-as-a-computer hypothesis.

All in all a stimulating work, if in need of updating.

Excellent.......2003-09-13

This book can be viewed as one of the first attempts to use results from psychology, neuroscience, computer science, and philosophy with the intent of gaining an understanding of how the mind/brain works, but all of this is done within the "computational mind" paradigm. The approach taken by the authors is one of the most honest of those in the literature, for throughout the book they are careful to note just how much evidence there is to support their position(s), and to what extent further work is to done. Philosophically speaking, the authors are clearly in the materialist camp, believing that Cartesian dualism does not cohere with current scientific knowledge. But they state that materialism is not an established fact, allowing the possibility, but not the probability, that dualism may in fact be true. They reject early on though any "arguments from ignorance" in their assertion that just because neuroscience does not have an explanation of consciousness, that such an explanation is impossible. The authors call the failure to be able to think of consciousness in terms of neuronal activity "intuition dissonance", and reject completely its efficacy in establishing the truth of the nature of the mind/brain.

The underlying theme in the book is to explain emergent properties as "high-level" effects that are dependent on "lower-level" phenomena, hence rejecting the thesis that they are "nomologically autonomous", i.e. that such a dependence cannot be done and is outside the domain of science. The science in this book recognizes its historical origins, and it is clear that the authors will not accept explanations of the mind/brain that do not involve scientific experimentation and analysis. Much has been done experimentally in neuroscience since this book was published, especially using the techniques of magnetic resonance imaging (MRI). A brief discussion of MRI is given in the Appendix of the book, but no doubt if the book were updated there would be a lengthy overview of it. The current experimental situation in neuroscience has led some to predict a total "reverse engineering" of the brain in the upcoming decades. This prediction is an optimistic one, but no doubt detailed knowledge of the brain will continue to accelerate, this being a sign of what the authors call "a remarkable time in the history of science".

The authors devote an entire chapter to the computational modeling of the brain, mostly of course dealing with the mathematics of neural networks. The approach in this chapter though is still at a level that would allow a general audience to follow it. Readers with a background in physics, especially statistical physics, will appreciate more the discussion on Hopfield networks and Boltzmann machines. Experimental results are inserted as graphs throughout the book, with detailed explanation. As a whole the discussion of the biology of the brain is purely descriptive, and the line drawings could stand some improvement.

The chapter on neuronal plasticity is the most interesting in the book, the authors viewing the brain as an entity that is continuously undergoing modification. Their stated goal in the chapter is to explain how the "local" property of plasticity can result in the "global" property of learning. Clearly intelligence to the authors is an emergent property, i.e. an object or device may be characterized as intelligent without its components being intelligent. Particularly interesting in this chapter was the discussion of the amnesia of a patient who underwent bilateral resection of mesial temporal lobe structures. The time scales of the patient's memory are striking: he remembered things before the surgery but could not remember things that happened a few minutes or hours ago, but could remember things within a minute in his past. The authors also mention the fascinating work of Antonio Damasio and his collaborators, this research being even more important at the present time. The scientific study of consciousness is just beginning and no doubt this study will give many surprises as it develops throughout the twenty-first century.

a great book.......2002-01-11

This extremely interesting book integrates our vast knowledge of neuroscience with computational models of perception, sensori-motor integration, memory etc.
For students of neuroscience, computer science and psychology this book is extremely important, because it gives you the necessary fundamentals of this field(namely computational neuroscience) so you can get to more advanced levels easily.
Understanding the book will need some background in higher mathematics (differential calculus).

Good summary of empirical and experimental neuroscience.......1996-11-12

This book is an excellent follow-up to "Engine of Reason, Seat of the Soul". It gets into the details of what's known about computational neuroscience and the working of the human brain (and other animals ' brains and nervous systems. Great summaries of specific "tricks" of brain processing, e.g., how vison works, etc.

Large-Scale Neuronal Theories of the Brain (Computational Neuroscience)

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Large-Scale Neuronal Theories of the Brain (Computational Neuroscience)
CHRISTOF KOCH
Manufacturer: M.I.T. PRESS
ProductGroup: Book
Binding: Hardcover

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Perceptual Neuroscience: The Cerebral Cortex

ASIN: 0262111837

Book Description

Large-Scale Neuronal Theories of the Brain brings together thirteen original contributions by some of the top scientists working in neuroscience today. It presents models and theories that will most likely shape and influence the way we think about the brain, the mind, and interactions between the two in the years to come. Chapters consider global theories of the brain from the bottom up -- providing theories that are based on real nerve cells, their firing properties, and their anatomical connections. This contrasts with attempts that have been made by psychologists and by theorists in the artificial intelligence community to understand the brain strictly from a psychological or computational point of view.

The authors encompass a broad background, from biophysics and electrophysiology to psychophysics, neurology, and computational vision. However, all the chapters focus on a common issue: the role of the primate (including human) cerebral cortex in memory, visual perception, focal attention, and awareness.

Contributors: Horace Barlow. Patricia Churchland, V. S. Ramachandran, and Terrence J. Sejnowski. Antonio R. Damasio and Hanna Damasio. Robert Desimone, Earl K. Miller, and Leonardo Chelazzi. Christof Koch and Francis Crick. Rodolfo R. Llinas and Urs Ribary. David Mumford. Tomaso Poggio and Anya Hurlbert. Michael I. Posner and Mary K. Rothbart. Wolf Singer. Charles F. Stevens. Shimon Ullman. David C. Van Essen, Charles W. Anderson, and Bruno A. Olshausen.

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Review from a Neurosurgeon

From Computer to Brain
William W. Lytton
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

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Fundamentals of Computational Neuroscience

ASIN: 0387955267

Book Description

Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

Customer Reviews:

Review from a Neurosurgeon.......2007-01-10

As someone who is interested in the subject of computational neuroscience, I found this book of great help. It is the best introduction to this very interesting and new discipline and well prepares the reader for more advanced reading of the subject.

Foundations of Language: Brain, Meaning, Grammar, Evolution

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One of the best books I've ever read
Worth browsing through
Theoretical linguistics you can sink your teeth into..

Foundations of Language: Brain, Meaning, Grammar, Evolution
Ray Jackendoff
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Paperback

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ASIN: 0199264376

Book Description

How does human language work? How do we put ideas into words that others can understand? Can linguistics shed light on the way the brain operates? Foundations of Language puts linguistics back at the centre of the search to understand human consciousness. Ray Jackendoff begins by surveying the developments in linguistics over the years since Noam Chomsky's Aspects of the Theory of Syntax. He goes on to propose a radical re-conception of how the brain processes language. This opens up vivid new perspectives on every major aspect of language and communication, including grammar, vocabulary, learning, the origins of human language, and how language relates to the real world. Foundations of Language makes important connections with other disciplines which have been isolated from linguistics for many years. It sets a new agenda for close cooperation between the study of language, mind, the brain, behaviour, and evolution.

Customer Reviews:

One of the best books I've ever read.......2004-06-19

This is an extremely good book on the various branches of linguistics, and cognitive linguistics, and their interrelations. While this is not my field and I cannot judge how fairly Jackendoff characterizes particular lines of theory and research (mindful here of an earlier review), never have I learned so much from a single book, and I left it with a profound respect for the care with which scholars of language go about their work, and the quality of the ideas resulting therefrom.

Worth browsing through.......2003-07-10

But not nearly as good as many people would have believe. Jackendoff has an unquestionably good broad grasp of mainstream contemporary research in grammar and cognitive psychology, and his approach to grammatical theory is way saner than mainstream generative grammar. But he is too dismissive of many things he evidently does not understand, like Cognitive Linguistics (which he calls "combinatorial", overusing the most overused word in this book), or anthropologically-oriented approaches to language. This is too bad, because he talks himself into a terrible solipsistic mess in his chapters on semantics (where he attacks "formal", truth-conditional semantics), which, as far as I can see, the only ideas that can get him out are those he dismisses the most casually.

Theoretical linguistics you can sink your teeth into.........2002-09-26

On almost every page of this book, I encountered an something which caused my to spontaneously exclaim "exactly!" or "Wow!". I'm wrapping up my masters degree in Linguistics, and had still not found a theoretical framework within which I would have wanted to do research. My exposure to mainstream generative theories (mostly GB and Minimalism) had left me with an empty feeling inside as well as a great number of nagging suspicions that something was fundamentally wrong here. I was starting to turn into a boring anti-Chomskian and was reading up on every lesser-known grammar theory I could find in hopes of finding confirmation of the ideas of language that were starting to take shape in my head. I was also totally perplexed as to how grammar theory was supposed to integrate with psycholinguistics, neurolinguistics, and evolutionary questions.
To make a long story short, reading this book amounted to the experience of having a premier linguist with decades of professional experience at the forefront of the field say: "Your suspicions are justified, you're not the only one with these questions, here are some possible answers...", and then lay out a theory that convinces through its clarity, descriptive and explanatory power, and psychological and neurological plausibility.
A side effect of reading this book is that I realized it is possible to be a nativist and a proponent of UG in spirit while also embracing advances made in connectionist, probabilistic, and statistical approaches to processing and language learning.
Thanks Ray!

Ug And External Systems: Language, Brain And Computation (Linguistik Aktuell / Linguistics Today)

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Ug And External Systems: Language, Brain And Computation (Linguistik Aktuell / Linguistics Today)

Manufacturer: John Benjamins Publishing Co
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ASIN: 1588116239

Thinking in Complexity: The Computational Dynamics of Matter, Mind, and Mankind

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very difficult subject; but intriguing ideas
understandable highest level science with cultural backg
Full but turgid catalogue of complexity phenomena

Thinking in Complexity: The Computational Dynamics of Matter, Mind, and Mankind
Klaus Mainzer
Manufacturer: Springer
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ASIN: 3540002391

Amazon.com

Chaos is cropping up everywhere these days. As it becomes ever more apparent that Newtonian mechanics is inadequate for modeling nonlinear systems, or systems that have too many degrees of freedom to handle easily, researchers in all fields are turning toward nonlinear dynamics as a refreshing alternative. This is a paradigm shift à la Kuhn, and Klaus Mainzer guides us through it with an astounding range of historical and scientific knowledge. From quantum physics to consciousness to economics, Mainzer shows us how thinking complexly can solve problems over which standard, linear thinking continually stumbles. Instead of simplifying, however, Mainzer revels in the complexity of complexity, so the reader should be prepared for advanced concepts in such varied fields as mathematics, physics, and economics. Difficult, but worthwhile reading.

Book Description

The theory of nonlinear, complex systems has become by now a proven problem-solving approach in the natural sciences. And it is now also recognized that many if not most of our social, ecological, economical and political problems are essentially of a global, complex and nonlinear nature. And it is now further accepted than any holistic perspective of the human mind and brain can hardly be achieved by any other approach. In this wide-ranging, scholarly but very concise treatment, physicist, computer scientist and philosopher Klaus Mainzer discusses, in essentially nontechnical language, the common framework behind these ideas and challenges. Emphasis is given to the evolution of new structures in natural and cultural systems and we are lead to see clearly how the new integrative approach can give insights not available from traditional reductionistic methods. The fifth edition enlarges and revises almost all sections and supplements an entirely new chapter on the complexity of economic systems.

From the reviews of the fourth edition:

"This book is ambitious, incredibly erudite with 22 pages of references, and is indisputably clearly and beautifully written and illustrated. It is perfectly suited to a first course on the science of complexity. Even beginners and young graduate students will have something to learn from this book." (Andre Hautot, Physicalia, Vol. 57 (3), 2005)

"All-in-all, this highly recommended book is a wonderful resource for intuitive basic ideas in the need of rigorous formulation." (Albert A. Mullin, Zentralblatt MATH, vol. 1046, 2004)

"Readers of this book will enjoy Mainzer's exposition, which is based on a tight coupling between classical and historical concepts from Plato and Aristotle to modern, mathematical and physical developments . Every chapter begins with a section designed to orient the reader to the perspective of philosophical developments through the ages pertinent to the topic at hand. The author takes pains to point out essential differences between classical science and the science of complexity. Thinking in Complexity is an outstandingly readable book." (Anutosh Moitra, The Industrial Physicist, August/September, 2004)

Customer Reviews:

very difficult subject; but intriguing ideas.......2006-01-19

[A review of the 4th Edition, 2003.]
This book studies complexity and nonlinearity across a diverse range of applications. Much of the book revolves around organic evolution and the evolution of a sentient mind. And how complexity analysis might aid in the understanding of these fields. Not the least in devising deeper forms of artificial intelligence.

So intriguing techniques like cellular automata and neural networks are studied. There is a fair amount of speculation as to how these and other topics might ultimately relate to sentience or consciousness. But the musings are grounded in solid science. Like that of a Hopfield system or a Boltzmann machine. This 4th edition is a good reflection of the boundaries of our knowledge.

understandable highest level science with cultural backg.......1999-06-16

The book covers a broad field - all parts in close connection with the others and its background in modern science and historic cultural connotations. The theoretical aspects are merged with lively explanations. Readable for the non-specialist, understandable for the average science-educated and meaningful for the specilaists, both in physical systems science and in philosophy. A top-notch guide through this topic of multidisciplinary novelties.

Full but turgid catalogue of complexity phenomena.......1998-02-25

This book is an extremely well-informed cataloguing of the many areas of human experience in which self-organisation and complexity phenomena play an important role. However the writer's style becomes very heavy as a result of transferring German constructions into English - so much so that I was forced to skim read many sections.

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