Computational Neuroscience Cortical Dynamics
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Computational Neuroscience Cortical Dynamics
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Author : Peter Erdi
language : en
Publisher: Springer
Release Date : 2004-12-27
Computational Neuroscience Cortical Dynamics written by Peter Erdi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-27 with Medical categories.
This book presents thoroughly revised tutorial papers based on lectures given by leading researchers at the 8th International Summer School on Neural Networks in Erice, Italy, in October/November 2003. The eight tutorial papers presented provide competent coverage of the field of cortical dynamics, consolidating recent theoretical and experimental results on the processing, transmission, and imprinting of information in the brain as well as on important functions of the cortical area, such as cortical rhythms, cortical neural plasticity, and their structural basis and functional significance. The book is divided in two topical sections on fundamentals of cortical dynamics and mathematical models of cortical dynamics.
Computational Neuroscience
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Author : Peter Erdi
language : en
Publisher:
Release Date : 2014-01-15
Computational Neuroscience written by Peter Erdi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Lectures In Supercomputational Neuroscience
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Author : Peter Graben
language : en
Publisher: Springer
Release Date : 2007-10-19
Lectures In Supercomputational Neuroscience written by Peter Graben and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-19 with Science categories.
Written from the physicist’s perspective, this book introduces computational neuroscience with in-depth contributions by system neuroscientists. The authors set forth a conceptual model for complex networks of neurons that incorporates important features of the brain. The computational implementation on supercomputers, discussed in detail, enables you to adapt the algorithm for your own research. Worked-out examples of applications are provided.
Nonlinear Dynamics In Computational Neuroscience
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Author : Fernando Corinto
language : en
Publisher: Springer
Release Date : 2018-06-19
Nonlinear Dynamics In Computational Neuroscience written by Fernando Corinto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-19 with Technology & Engineering categories.
This book provides an essential overview of computational neuroscience. It addresses a broad range of aspects, from physiology to nonlinear dynamical approaches to understanding neural computation, and from the simulation of brain circuits to the development of engineering devices and platforms for neuromorphic computation. Written by leading experts in such diverse fields as neuroscience, physics, psychology, neural engineering, cognitive science and applied mathematics, the book reflects the remarkable advances that have been made in the field of computational neuroscience, an emerging discipline devoted to the study of brain functions in terms of the information-processing properties of the structures forming the nervous system. The contents build on the workshop “Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT,” which was held in Torino, Italy in September 2015.
Computational Neuroscience
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Author : Eric L. Schwartz
language : en
Publisher: MIT Press
Release Date : 1993-08-26
Computational Neuroscience written by Eric L. Schwartz and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-08-26 with Computational neuroscience categories.
The thirty original contributions in this book provide a working definition of"computational neuroscience" as the area in which problems lie simultaneously within computerscience and neuroscience. They review this emerging field in historical and philosophical overviewsand in stimulating summaries of recent results. Leading researchers address the structure of thebrain and the computational problems associated with describing and understanding this structure atthe synaptic, neural, map, and system levels.The overview chapters discuss the early days of thefield, provide a philosophical analysis of the problems associated with confusion between brainmetaphor and brain theory, and take up the scope and structure of computationalneuroscience.Synaptic-level structure is addressed in chapters that relate the properties ofdendritic branches, spines, and synapses to the biophysics of computation and provide a connectionbetween real neuron architectures and neural network simulations.The network-level chapters take upthe preattentive perception of 3-D forms, oscillation in neural networks, the neurobiologicalsignificance of new learning models, and the analysis of neural assemblies and local learningrides.Map-level structure is explored in chapters on the bat echolocation system, cat orientationmaps, primate stereo vision cortical cognitive maps, dynamic remapping in primate visual cortex, andcomputer-aided reconstruction of topographic and columnar maps in primates.The system-level chaptersfocus on the oculomotor system VLSI models of early vision, schemas for high-level vision,goal-directed movements, modular learning, effects of applied electric current fields on corticalneural activity neuropsychological studies of brain and mind, and an information-theoretic view ofanalog representation in striate cortex.Eric L. Schwartz is Professor of Brain Research and ResearchProfessor of Computer Science, Courant Institute of Mathematical Sciences, New York UniversityMedical Center. Computational Neuroscience is included in the System Development FoundationBenchmark Series.
Principles Of Brain Dynamics
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Author : Mikhail I. Rabinovich
language : en
Publisher: MIT Press
Release Date : 2012-07-06
Principles Of Brain Dynamics written by Mikhail I. Rabinovich and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-06 with Medical categories.
Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field. 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.
Correlated Neuronal Activity And Its Relationship To Coding Dynamics And Network Architecture
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Author : Tatjana Tchumatchenko
language : en
Publisher: Frontiers E-books
Release Date : 2014-12-03
Correlated Neuronal Activity And Its Relationship To Coding Dynamics And Network Architecture written by Tatjana Tchumatchenko and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-03 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.
Correlated activity in populations of neurons has been observed in many brain regions and plays a central role in cortical coding, attention, and network dynamics. Accurately quantifying neuronal correlations presents several difficulties. For example, despite recent advances in multicellular recording techniques, the number of neurons from which spiking activity can be simultaneously recorded remains orders magnitude smaller than the size of local networks. In addition, there is a lack of consensus on the distribution of pairwise spike cross correlations obtained in extracellular multi-unit recordings. These challenges highlight the need for theoretical and computational approaches to understand how correlations emerge and to decipher their functional role in the brain.
The Computational Brain
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Author : Patricia Smith Churchland
language : en
Publisher: MIT Press
Release Date : 1992
The Computational Brain written by Patricia Smith Churchland and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Anatomy categories.
"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."--Jacket.
Brain Dynamics
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Author : Hermann Haken
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-11-22
Brain Dynamics written by Hermann Haken and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-22 with Science categories.
This book addresses a large variety of models in mathematical and computational neuroscience. It is written for the experts as well as for graduate students wishing to enter this fascinating field of research. The author studies the behaviour of large neural networks composed of many neurons coupled by spike trains. An analysis of phase locking via sinusoidal couplings leading to various kinds of movement coordination is included.
Neural Masses And Fields Modelling The Dynamics Of Brain Activity
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Author : Karl Friston
language : en
Publisher: Frontiers Media SA
Release Date : 2015-05-25
Neural Masses And Fields Modelling The Dynamics Of Brain Activity written by Karl Friston and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-25 with Differential equations categories.
Biophysical modelling of brain activity has a long and illustrious history and has recently profited from technological advances that furnish neuroimaging data at an unprecedented spatiotemporal resolution. Neuronal modelling is a very active area of research, with applications ranging from the characterization of neurobiological and cognitive processes, to constructing artificial brains in silico and building brain-machine interface and neuroprosthetic devices. Biophysical modelling has always benefited from interdisciplinary interactions between different and seemingly distant fields; ranging from mathematics and engineering to linguistics and psychology. This Research Topic aims to promote such interactions by promoting papers that contribute to a deeper understanding of neural activity as measured by fMRI or electrophysiology. In general, mean field models of neural activity can be divided into two classes: neural mass and neural field models. The main difference between these classes is that field models prescribe how a quantity characterizing neural activity (such as average depolarization of a neural population) evolves over both space and time as opposed to mass models, which characterize activity over time only; by assuming that all neurons in a population are located at (approximately) the same point. This Research Topic focuses on both classes of models and considers several aspects and their relative merits that: span from synapses to the whole brain; comparisons of their predictions with EEG and MEG spectra of spontaneous brain activity; evoked responses, seizures, and fitting data - to infer brain states and map physiological parameters.