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From Neuron To Cognition Via Computational Neuroscience

Author: Michael A. Arbib
Publisher: MIT Press
ISBN: 0262335271
Size: 56.43 MB
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This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience -- methods for modeling the causal interactions underlying neural systems -- complements empirical research in advancing the understanding of brain and behavior. The chapters -- all by leaders in the field, and carefully integrated by the editors -- cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language -- the core of human cognition.The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter).ContributorsMichael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille

Computational Neuroscience

Author: Hanspeter Mallot
Publisher: Springer Science & Business Media
ISBN: 3319008617
Size: 71.90 MB
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Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.

Principles Of Brain Dynamics

Author: Mikhail I. Rabinovich
Publisher: MIT Press
ISBN: 0262304651
Size: 19.79 MB
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The consideration of time or dynamics is fundamental for all aspects of mental activity -- perception, cognition, and emotion -- because the main feature of brain activity is the continuous change of the underlying brain states even in a constant environment. The application of nonlinear dynamics to the study of brain activity began to flourish in the 1990s when combined with empirical observations from modern morphological and physiological observations. This book offers perspectives on brain dynamics that draw on the latest advances in research in the field. It includes contributions from both theoreticians and experimentalists, offering an eclectic treatment of fundamental issues. Topics addressed range from experimental and computational approaches to transient brain dynamics to the free-energy principle as a global brain theory. The book concludes with a short but rigorous guide to modern nonlinear dynamics and their application to neural dynamics.

Neural Control Engineering

Author: Steven J. Schiff
Publisher: MIT Press
ISBN: 0262015374
Size: 63.90 MB
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How powerful new methods in nonlinear control engineering can be applied to neuroscience, from fundamental model formulation to advanced medical applications.

The Computational Brain

Author: Patricia S. Churchland
Publisher: MIT Press
ISBN: 0262339668
Size: 24.85 MB
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Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research.This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.

Computational Explorations In Cognitive Neuroscience

Author: Randall C. O'Reilly
Publisher: MIT Press
ISBN: 9780262650540
Size: 60.61 MB
Format: PDF
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This text, based on a course taught by Randall O'Reilly and Yuko Munakata over thepast several years, provides an in-depth introduction to the main ideas in the computationalcognitive neuroscience.

Methods In Neuronal Modeling

Author: Christof Koch
Publisher: MIT Press
ISBN: 9780262112314
Size: 49.58 MB
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This book serves as a handbook of computational methods and techniques for modeling the functional properties of single and groups of nerve cells.

The Neural Simulation Language

Author: Alfredo Weitzenfeld
Publisher: MIT Press
ISBN: 9780262731492
Size: 18.74 MB
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The Neural Simulation Language (NSL), developed by Alfredo Weitzenfeld, MichaelArbib, and Amanda Alexander, provides a simulation environment for modular brain modeling. NSL is anobject-oriented language offering object-oriented protocols applicable to all levels of neuralsimulation. One of NSL's main strengths is that it allows for realistic modeling of the anatomy ofmacroscopic brain structures.The book is divided into two parts. The first part presents an overviewof neural network and schema modeling, a brief history of NSL, and a detailed discussion of the newversion, NSL 3.0. It includes tutorials on several basic schema and neural network models. Thesecond part presents models built in NSL by researchers from around the world, including those forconditional learning, face recognition, associative search networks, and visuomotor coordination.Each chapter provides an explanation of a model, an overview of the NSL 3.0 code, and arepresentative set of simulation results.