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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. 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 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 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. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. 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. A Bradford Book Computational Neuroscience series
560 pages, Paperback
First published January 1, 1992
8 people are currently reading
751 people want to read
About the author
Patricia S. Churchland
16 books212 followersPatricia Smith Churchland (born July 16, 1943 in Oliver, British Columbia, Canada) is a Canadian-American philosopher working at the University of California, San Diego (UCSD) since 1984. She is currently a professor at the UCSD Philosophy Department, an adjunct professor at the Salk Institute for Biological Studies, and an associate of the Computational Neuroscience Laboratory (Sejnowski Lab) at the Salk Institute. She won a MacArthur prize in 1991. Educated at the University of British Columbia, the University of Pittsburgh, and the University of Oxford (B.Phil.). She taught philosophy at the University of Manitoba from 1969 to 1984 and is the wife of philosopher Paul Churchland.
Churchland has focused on the interface between neuroscience and philosophy. According to her, philosophers are increasingly realizing that to understand the mind one must understand the brain. She is associated with a school of thought called eliminativism or eliminative materialism, which argues that folk psychology concepts such as belief, free will, and consciousness will likely need to be revised as science understands more about the nature of brain function. She is also called a naturalist, because she thinks scientific research is the best basis for understanding the nature of the mind. Her recent work focuses also on neuroethics, and attempts to understand choice, responsibility and the basis of moral norms in terms of brain function, brain evolution, and brain-culture interactions.
She was interviewed along with her husband Paul Churchland for the book Conversations on Consciousness by Susan Blackmore, 2006.
She attended and was a speaker at the Beyond Belief symposium on November 2006 and November 2007.
Patricia and her husband are noted for their attempts to apply their philosophical positions in their daily life. Emotions and feelings, for instance, are eschewed in favour of more precise formulations, such as the following which describes the state of Patricia after a hectic meeting:
"Paul, don't speak to me, my serotonin levels have hit bottom, my brain is awash in glucocorticoids, my blood vessels are full of adrenaline, and if it weren't for my endogenous opiates I'd have driven the car into a tree on the way home. My dopamine levels need lifting."
Churchland has focused on the interface between neuroscience and philosophy. According to her, philosophers are increasingly realizing that to understand the mind one must understand the brain. She is associated with a school of thought called eliminativism or eliminative materialism, which argues that folk psychology concepts such as belief, free will, and consciousness will likely need to be revised as science understands more about the nature of brain function. She is also called a naturalist, because she thinks scientific research is the best basis for understanding the nature of the mind. Her recent work focuses also on neuroethics, and attempts to understand choice, responsibility and the basis of moral norms in terms of brain function, brain evolution, and brain-culture interactions.
She was interviewed along with her husband Paul Churchland for the book Conversations on Consciousness by Susan Blackmore, 2006.
She attended and was a speaker at the Beyond Belief symposium on November 2006 and November 2007.
Patricia and her husband are noted for their attempts to apply their philosophical positions in their daily life. Emotions and feelings, for instance, are eschewed in favour of more precise formulations, such as the following which describes the state of Patricia after a hectic meeting:
"Paul, don't speak to me, my serotonin levels have hit bottom, my brain is awash in glucocorticoids, my blood vessels are full of adrenaline, and if it weren't for my endogenous opiates I'd have driven the car into a tree on the way home. My dopamine levels need lifting."
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Displaying 1 - 8 of 8 reviews
January 26, 2016
My background is Neuroscience and during college I took a class with Terrance Sejnowski one of the co-authors and was blown away during every lecture. He made it the textbook for Computational Neurobiology at UC San Diego. Very cutting edge computational neuroscience with unparalleled depth which I was luckily able to navigate with the help of the professor/co-author. It goes from the basics to the bleeding edge really quickly yet leaves nothing unexplained. Not a fun book to pick up and read unless you are a computational neurobiologist (but it does have a lot of diagrams and explanations if you are unfamiliar). This is the book that inspired me to further research the obscure field of optogenetics. Terrance if you see this... Thanks for letting me turn my optogenetics paper almost 6 months late! =)
October 27, 2007
This isn't my field, and I didn't grasp the entire book, but it's amazing how much we've learned about the brain in the last 20 years. I don't think the consciousness problem has been figured out yet, despite Dennett's "Consciousness Explained" and Pinker's "How the Mind Works," but at this point the more you know about cognitive neuroscience, the more impossible it is to believe that a mind (human or divine or angelic or whatever) could ever exist (that is, happen) without a brain.
August 22, 2024
THE COMPLEXITIES OF THE BRAIN AS FROM "THE DYNAMICS OF NEURAL NETWORKS”
Patricia Smith Churchland (born 1943) is a Canadian-American philosopher and Professor of Philosophy Emerita at the University of California, San Diego. She has also written books such as 'Neurophilosophy: Toward a Unified Science of the Mind-Brain,' 'Brain-Wise,' 'Touching a Nerve: The Self as Brain,' etc. Terrence Sejnowski is a neurobiologist who has also written 'Massively-Parallel Architectures for Automatic Recognition of Visual Speech Signals.'
They wrote in the Preface to this 1992 book, "The idea that brains are computational in nature has spawned a range of explanatory hypotheses in theoretical neurobiology. This book represents one slant on current computational research relevant to neurobiology, a slant both on the conceptual foundations and the benchmark studies... The questions that became pivotal... were questions that have been biting our heels more or less incessantly. The book is thus shaped by what has bothered or beguiled us, individually and jointly." (Pg. ix)
They begin, "it appears highly probable that psychological processes are in fact processes of the physical brain, not, as Descartes concluded, processes of a nonphysical soul or mind... since Cartesian dualism is not taken very seriously either in mainstream philosophy or mainstream neuroscience, it is not necessary to repeat the details of the arguments here. Suffice it to say that the Cartesian hypothesis fails to cohere with current physics, chemistry, evolutionary biology, molecular biology, embryology, immunology, and neuroscience. To be sure, materialism is not an established fact... It is possible, therefore, that ... dualism might actually be true... [but] materialism, like Darwinian evolution, is the more probable working hypothesis. That being so, it does not seem worthwhile to modify the basic neuroscience research program and its scaffolding of physicalist presuppositions to accommodate the Cartesian hypothesis, though scientific tolerance counsels that the door not be closed until the facts ... truly close it." (Pg. 1-2)
They outline, "The working hypothesis underlying this book is that emergent properties are high-level effects that depend on lower-level phenomena in some systematic way... Although a given phenomenon ... cannot NOW be explained, it might yield to explanation as time and science go on. Whether it does or not is a matter of empirical fact, not a matter of a priori divination. Searching for reductive explanations of emergent properties ... means only that the betting man keeps going." (Pg. 2-3) They add, "The overarching contention of this book is that knowledge of the molecular and cellular levels is essential, but on its own is not enough... Complex effects... are the outcome of the dynamics of neural networks... it is dynamical, not a simple wind-up doll affair." (Pg. 4)
They explain, "As we use the term, 'computational neuroscience' aims for biological realism in computational models of neural networks... we view the blurring of the disciplinary boundaries between neuroscience, computer science, and psychology as a healthy development to be wisely encouraged... The expression 'computational' in computational neuroscience reflects the role of the computer as a research tool in modeling complex systems such as networks, ganglia, and brains." (Pg. 6-7)
The conclude on the note, "we have dwelt upon the deep and difficult problems facing brain research... In step with the deep and difficult ETHICAL questions concerning what to do with the knowledge, we can expect to ponder matters of human agency and responsibility, what justice requires in dealing with antisocial behavior, whether and how to intervene in the nervous systems nature supplies, what is appropriate in neural transplants both synthetic and real---just for starters. Neuroscience PER SE cannot tell us what OUGHT to be done, but only how things ARE in the brain... The ethical questions... are thus more convoluted and ticklish than elsewhere in science, because they concern manipulating efficiently and directly the very thing that makes us what we are---the very thing that reasons about scientific and ethical issues... We shall, all of us, need to keep our wits about us." (Pg. 425-426)
This book will be of interest to students of cognitive science, and (perhaps) of the philosophy of mind.
Patricia Smith Churchland (born 1943) is a Canadian-American philosopher and Professor of Philosophy Emerita at the University of California, San Diego. She has also written books such as 'Neurophilosophy: Toward a Unified Science of the Mind-Brain,' 'Brain-Wise,' 'Touching a Nerve: The Self as Brain,' etc. Terrence Sejnowski is a neurobiologist who has also written 'Massively-Parallel Architectures for Automatic Recognition of Visual Speech Signals.'
They wrote in the Preface to this 1992 book, "The idea that brains are computational in nature has spawned a range of explanatory hypotheses in theoretical neurobiology. This book represents one slant on current computational research relevant to neurobiology, a slant both on the conceptual foundations and the benchmark studies... The questions that became pivotal... were questions that have been biting our heels more or less incessantly. The book is thus shaped by what has bothered or beguiled us, individually and jointly." (Pg. ix)
They begin, "it appears highly probable that psychological processes are in fact processes of the physical brain, not, as Descartes concluded, processes of a nonphysical soul or mind... since Cartesian dualism is not taken very seriously either in mainstream philosophy or mainstream neuroscience, it is not necessary to repeat the details of the arguments here. Suffice it to say that the Cartesian hypothesis fails to cohere with current physics, chemistry, evolutionary biology, molecular biology, embryology, immunology, and neuroscience. To be sure, materialism is not an established fact... It is possible, therefore, that ... dualism might actually be true... [but] materialism, like Darwinian evolution, is the more probable working hypothesis. That being so, it does not seem worthwhile to modify the basic neuroscience research program and its scaffolding of physicalist presuppositions to accommodate the Cartesian hypothesis, though scientific tolerance counsels that the door not be closed until the facts ... truly close it." (Pg. 1-2)
They outline, "The working hypothesis underlying this book is that emergent properties are high-level effects that depend on lower-level phenomena in some systematic way... Although a given phenomenon ... cannot NOW be explained, it might yield to explanation as time and science go on. Whether it does or not is a matter of empirical fact, not a matter of a priori divination. Searching for reductive explanations of emergent properties ... means only that the betting man keeps going." (Pg. 2-3) They add, "The overarching contention of this book is that knowledge of the molecular and cellular levels is essential, but on its own is not enough... Complex effects... are the outcome of the dynamics of neural networks... it is dynamical, not a simple wind-up doll affair." (Pg. 4)
They explain, "As we use the term, 'computational neuroscience' aims for biological realism in computational models of neural networks... we view the blurring of the disciplinary boundaries between neuroscience, computer science, and psychology as a healthy development to be wisely encouraged... The expression 'computational' in computational neuroscience reflects the role of the computer as a research tool in modeling complex systems such as networks, ganglia, and brains." (Pg. 6-7)
The conclude on the note, "we have dwelt upon the deep and difficult problems facing brain research... In step with the deep and difficult ETHICAL questions concerning what to do with the knowledge, we can expect to ponder matters of human agency and responsibility, what justice requires in dealing with antisocial behavior, whether and how to intervene in the nervous systems nature supplies, what is appropriate in neural transplants both synthetic and real---just for starters. Neuroscience PER SE cannot tell us what OUGHT to be done, but only how things ARE in the brain... The ethical questions... are thus more convoluted and ticklish than elsewhere in science, because they concern manipulating efficiently and directly the very thing that makes us what we are---the very thing that reasons about scientific and ethical issues... We shall, all of us, need to keep our wits about us." (Pg. 425-426)
This book will be of interest to students of cognitive science, and (perhaps) of the philosophy of mind.
October 11, 2019
My ratings of books on Goodreads are solely a crude ranking of their utility to me, and not an evaluation of literary merit, entertainment value, social importance, humor, insightfulness, scientific accuracy, creative vigor, suspensefulness of plot, depth of characters, vitality of theme, excitement of climax, satisfaction of ending, or any other combination of dimensions of value which we are expected to boil down through some fabulous alchemy into a single digit.
April 20, 2022
My ratings of books on Goodreads are solely a crude ranking of their utility to me, and not an evaluation of literary merit, entertainment value, social importance, humor, insightfulness, scientific accuracy, creative vigor, suspensefulness of plot, depth of characters, vitality of theme, excitement of climax, satisfaction of ending, or any other combination of dimensions of value which we are expected to boil down through some fabulous alchemy into a single digit.
February 20, 2014
This text is a comprehensive survey of the fascinating field of computational neuroscience written by one of its founders. it is a bit of a slog to get through, but well worth the effort. Most of the technical details are confined to the central chapters, which discuss specific neural pathways effecting object recognition, memory/learning, and sensorimotor coordination; the overview chapters that bracket them are an excellent overview of the current state of neuroscience and the insights that have been gained through its interaction with computer science and are, by themselves, worth the price of admission. It turns out that the mathematical metaphors of vectors and transformation matrices (don't worry, it's not as hard as it sounds) yield exciting insights when applied to human cognition.
July 26, 2016
A neat book on neurophilosophy and building biologically realistic models of neurons and neuron populations. Asks questions about what is necessary and sufficient for cognition, and what the future of cognitive modeling holds.
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December 9, 2013this book just push psychology to a new level:-)
Displaying 1 - 8 of 8 reviews