Synopses & Reviews
andlt;Pandgt;Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.andlt;/Pandgt;
Review
Not only does the book set a high standard for theoretical neuroscience, it defines the field. < b=""> M. Brandon Westover <> - Philosophical Psychology
Review
andquot;Not only does the book set a high standard for theoretical neuroscience, it defines the field.andquot;
-- Dmitri Chklovskii, Neuron
Review
It will not be surprising if this book becomes the standard text for students and researchers entering theoretical neuroscience for years to come. P. Read Montague, Professor, Division of Neuroscience, and Director, Center for Theoretical Neuroscience, Baylor College of Medicine
Review
Upon the ruins of Freud's failed attempt to construct a universal theory of mind, Hobson builds a catholic, brain-based edifice to account for the phenomenology of awake consciousness, sleep, and dreams in sickness and health. Its cornerstone -- that dreaming, psychosis, and psychedelic experiences are closely related phenomena caused by specific alterations in the brain's neuromodulatory systems -- allows him to explain a dizzying variety of altered states -- from hypnosis to lucid dreaming, from out-of-body to religious experiences, mind-altering drugs and so on -- within a single framework. < b=""> Bard Ermentrout <> , Department of Mathematics, University of Pittsburgh
Review
Peter Dayan and L.F. Abbott have crafted an excellent introduction to the various methods of modeling nervous system function. The chapters dealing with neural coding and information theory are particularly welcome because these are new areas that are not well represented in existing texts. The MIT Press
Review
Dayan and Abbott inspire us with a work of tremendous breadth, and each chapter is more exciting than the next. Everyone with an interest in neuroscience will want to read this book. A truly remarkable effort by two of the leaders in the field. Phillip S. Ulinski
Review
An excellent book. There are a few volumes already available in theoretical neuroscience but none have the scope that this one does. < b=""> P. Read Montague <> , Professor, Division of Neuroscience, and Director, Center for Theoretical Neuroscience, Baylor College of Medicine
Review
Theoretical Neuroscience provides a rigorous introduction to how neurons code, compute, and adapt. It is a remarkable synthesis of advances from many areas of neuroscience into a coherent computational framework. This book sets the standards for a new generation of modelers. Bard Ermentrout, Department of Mathematics, University of Pittsburgh
Review
The first comprehensive textbook on computational neuroscience. The topics covered span the gamut from biophysical faithful single cell models to neural networks, from the way nervous systems encode information in spike trains to how this information might be decoded, and from synaptic plasticity to supervised and unsupervised learning. And all of this is presented in a sophisticated yet accessible manner. A must buy for anybody who cares about the way brains compute. Terrence J. Sejnowski, Howard Hughes Medical Institute, Salk Institute for Biological Studies, and University of California, San Diego
Review
Theoretical Neuroscience marks a milestone in the scientific maturation of integrative neuroscience. In the last decade, computational and mathematical modelling have developed into an integral part of the field, and now we finally have a textbook that reflects the changes in the way our science is being done. It will be a standard source of knowledge for the coming generation of students, both theoretical and experimental. I urge anyone who wants to be part of the development of this science in the next decades to get this book. Read it, and let your students read it. Christof Koch, Lois and Victor Troendle Professor of Cognitive and Behavioral Biology, California Institute of Technology
Review
The more we learn about the brain, the more we are coming to realize that understanding its development will be a key tounlocking its functions, especially its ability to adapt to new environments. The wide range of levels of development that can be studied, from the molecular to the cognitive, are described in this book by some of the leading researchers in this growing field of computational neural development. John Hertz, Nordita (Nordic Institute for Theoretical Physics), Denmark
Review
"Independent component analysis is a recent and powerful addition to the methods that scientists and engineers have available toexplore large data sets in high-dimensional spaces. This book is a clearly written introduction to the foundations of ICA and the practical issues that arise in applying it to a wide range of problems."--Terrence J. Sejnowski, Howard Hughes Medical Institute, Salk Institute for Biological Studies, and University of California, San Diego
Review
Eugene Izhikevich has written an excellent introduction to the application of nonlinear dynamics to the spiking patterns of neurons. There are dozens of clear illustrations and hundreds of exercises ranging from the very easy to Ph.D.-level questions. The book will be suitable for mathematicians and physicists who want to jump into this exciting field as well as for neuroscientists who desire a deeper understanding of the utility of nonlinear dynamics applied to biology. The MIT Press
Review
andlt;Pandgt;"Eugene Izhikevich has written an excellent introduction to the application of nonlinear dynamics to the spiking patterns of neurons. There are dozens of clear illustrations and hundreds of exercises ranging from the very easy to Ph.D.-level questions. The book will be suitable for mathematicians and physicists who want to jump into this exciting field as well as for neuroscientists who desire a deeper understanding of the utility of nonlinear dynamics applied to biology."--Bard Ermentrout, Department of Mathematics, University of Pittsburghandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"Upon the ruins of Freud's failed attempt to construct a universal theory of mind, Hobson builds a catholic, brain-based edifice to account for the phenomenology of awake consciousness, sleep, and dreams in sickness and health. Its cornerstone--that dreaming, psychosis, and psychedelic experiences are closely related phenomena caused by specific alterations in the brain's neuromodulatory systems--allows him to explain a dizzying variety of altered states--from hypnosis to lucid dreaming, from out-of-body to religious experiences, mind-altering drugs and so on--within a single framework."--Christof Koch, Lois and Victor Troendle Professor of Cognitive and Behavioral Biology, California Institute of Technologyandlt;/Pandgt; The MIT Press The MIT Press
Review
andlt;Pandgt;"It will not be surprising if this book becomes the standard text for students and researchers entering theoretical neuroscience for years to come." M. Brandon Westover Philosophical Psychologyandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"Not only does the book set a high standard for theoretical neuroscience, it defines the field." Dmitri Chklovskii Neuronandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"Peter Dayan and L. F. Abbott have crafted an excellent introduction to the various methods of modeling nervous system function. The chapters dealing with neural coding and information theory are particularly welcome because these are new areas that are not well represented in existing texts."--Phillip S. Ulinski, Committee on Computational Neuroscience, University of Chicagoandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"Dayan and Abbott inspire us with a work of tremendous breadth, and each chapter is more exciting than the next. Everyone with an interest in neuroscience will want to read this book. A truly remarkable effort by two of the leaders in the field."--P. Read Montague, Professor, Division of Neuroscience, and Director, Center for Theoretical Neuroscience, Baylor College of Medicineandlt;/Pandgt; The MIT Press
Review
An excellent book. There are a few volumes already available in theoretical neuroscience but none have the scope that this one does. < b=""> Dmitri Chklovskii <> - Neuron
Review
andlt;Pandgt;"Theoretical Neuroscience provides a rigorous introduction to how neurons code, compute, and adapt. It is a remarkable synthesis of advances from many areas of neuroscience into a coherent computational framework. This book sets the standards for a new generation of modelers."--Terrence J. Sejnowski, Howard Hughes Medical Institute, Salk Institute for Biological Studies, and University of California, San Diegoandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"The first comprehensive textbook on computational neuroscience. The topics covered span the gamut from biophysical faithful single cell models to neural networks, from the way nervous systems encode information in spike trains to how this information might be decoded, and from synaptic plasticity to supervised and unsupervised learning. And all of this is presented in a sophisticated yet accessible manner. A must buy for anybody who cares about the way brains compute."--Christof Koch, Lois and Victor Troendle Professor of Cognitive and Behavioral Biology, California Institute of Technologyandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"Theoretical Neuroscience marks a milestone in the scientific maturation of integrative neuroscience. In the last decade, computational and mathematical modelling have developed into an integral part of the field, and now we finally have a textbook that reflects the changes in the way our science is being done. It will be a standard source of knowledge for the coming generation of students, both theoretical and experimental. I urge anyone who wants to be part of the development of this science in the next decades to get this book. Read it, and let your students read it."--John Hertz, Nordita (Nordic Institute for Theoretical Physics), Denmarkandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;"The more we learn about the brain, the more we are coming to realize that understanding its development will be a key tounlocking its functions, especially its ability to adapt to new environments. The wide range of levels of development that can be studied, from the molecular to the cognitive, are described in this book by some of the leading researchers in this growing field of computational neural development."--Terrence J. Sejnowski, Howard Hughes Medical Institute, Salk Institute for Biological Studies, and University of California, San Diegoandlt;/Pandgt;
Review
Theoretical Neuroscience provides a rigorous introduction to how neurons code, compute, and adapt. It is a remarkable synthesis of advances from many areas of neuroscience into a coherent computational framework. This book sets the standards for a new generation of modelers. Christof Koch, Lois and Victor Troendle Professor of Cognitive and Behavioral Biology, California Institute of Technology
Synopsis
Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.
The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.
Synopsis
Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.
Synopsis
The construction and analysis of mathematical and computational models of neural systems.
About the Author
Peter Dayan is Professor and Director of the Gatsby Computational Neuroscience Unit at University College London.Larry Abbott is Professor of Neuroscience and Co-Director of the Center for Theoretical Neuroscience at Columbia University.