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Modeling Neural Circuits Made Simple With Python

by Robert Rosenbaum

~~119,25€~~ 107,33€ 10% OFF

 An accessible undergraduate textbook in computational neuroscience that provides an introduction to the mathematical and computational modeling of neurons and networks of neurons.Understanding the brain is a major frontier of modern science. Given the complexity of neural circuits, advancing that understanding requires mathematical and computational approaches. This accessible undergraduate textbook in computational neuroscience provides an introduction to the mathematical and computational modeling of neurons and networks of neurons. Starting with the biophysics of single neurons, Robert Rosenbaum incrementally builds to explanations of neural coding, learning, and the relationship between biological and artificial neural networks. Examples with real neural data demonstrate how computational models can be used to understand phenomena observed in neural recordings. Based on years of classroom experience, the material has been carefully streamlined to provide all the content needed to build a foundation for modeling neural circuits in a one-semester course.• Proven in the classroom • Example-rich, student-friendly approach • Includes Python code and a mathematical appendix reviewing the requisite background in calculus, linear algebra, and probability • Ideal for engineering, science, and mathematics majors and for self-study
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Principles Of Brain Dynamics - Global State Interactions

198,75€ + 10% CARD

 Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field.
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Biological Learning And Control - How The Brain Builds Representations, Predicts Events, And Makes Decisions

by Reza Shadmehr e Sandro Mussa-Ivaldi

159,00€ + 10% CARD

 A novel theoretical framework that describes a possible rationale for the regularity in how we move, how we learn, and how our brain predicts events.
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Bayesian Brain - Probabilistic Approaches To Neural Coding

92,75€ + 10% CARD

 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. This work discusses how Bayesian concepts can be used for interpretation of such neurobiological data as neural spikes.
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Graphical Models - Foundations Of Neural Computation

99,38€ + 10% CARD

 This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research.
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Neurobiology Of Neural Networks

59,63€ + 10% CARD

 This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists to participate in constructing the next generation of neural networks. Individual chapters were commissioned from selected authors to bridge the gap between present neural network models and the needs of neurophysiologists who are trying to use these models as part of their research on how the brain works.Contents Introduction: Toward Neural Neural Networks, Daniel Gardner • Two Principles of Brain Organization: A Challenge for Artificial Neural Networks, Charles F. Stevens • Static Determinants of Synaptic Strength, Daniel Gardner • Learning Rules From Neurobiology, Douglas A. Baxter and John H. Byrne • Realistic Network Models of Distributed Processing in the Leech, Shawn R. Lockery and Terrence J. Sejnowski • Neural and Peripheral Dynamics as Determinants of Patterned Motor Behavior, Hillel J. Chiel and Randall D. Beer • Dynamic Neural Network Models of Sensorimotor Behavior, Eberhard E. Fetz
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Unsupervised Learning - Foundations Of Neural Computation

79,50€ + 10% CARD

 Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
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Theoretical Foundation Of Dendritic Function - The Collected Papers Of Wilfrid Rall With Commentaries

79,50€ + 10% CARD

 This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall''s colleagues and other leading neuroscientists.Wilfrid Rall was a pioneer in establishing the integrative functions of neuronal dendrites that have provided a foundation for neurobiology in general and computational neuroscience in particular. This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall''s colleagues and other leading neuroscientists. It brings together Rall''s work over more than forty years, including his first papers extending cable theory to complex dendritic trees, his ground-breaking paper introducing compartmental analysis to computational neuroscience, and his studies of synaptic integration in motoneurons, dendrodendritic interactions, plasticity of dendritic spines, and active dendritic properties. Today it is well known that the brain''s synaptic information is processed mostly in the dendrites where many of the plastic changes underlying learning and memory take place. It is particularly timely to look again at the work of a major creator of the field, to appreciate where things started and where they have led, and to correct any misinterpretations of Rall''s work. The editors'' introduction highlights the major insights that were gained from Rall''s studies as well as from those of his collaborators and followers. It asks the questions that Rall proposed during his scientific career and briefly summarizes the answers.The papers include commentaries by Milton Brightman, Robert E. Burke, William R. Holmes, Donald R. Humphrey, Julian J. B. Jack, John Miller, Stephen Redman, John Rinzel, Idan Segev, Gordon M. Shepherd, and Charles Wilson.
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Fundamentals Of Neural Network Modeling - Neuropsychology And Cognitive Neuroscience

159,00€ + 10% CARD

 Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes.
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Computational Brain

by Patricia S. Churchland e Terrence J. Sejnowski

90,10€ + 10% CARD

 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.
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Neural Control Engineering - The Emerging Intersection Between Control Theory And Neuroscience

by Steven J. Schiff

212,00€ + 10% CARD

 How powerful new methods in nonlinear control engineering can be applied to neuroscience, from fundamental model formulation to advanced medical applications.
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Dynamical Systems In Neuroscience - The Geometry Of Excitability And Bursting

by Eugene M. Izhikevich

132,50€ + 10% CARD

 Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition.
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Computational Brain

by Patricia S. Churchland e Terrence J. Sejnowski

90,10€ + 10% CARD

 An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists.
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Visual Cortex And Deep Networks - Learning Invariant Representations

by Fabio Anselmi e Tomaso A. Poggio

92,75€ + 10% CARD

 A mathematical framework that describes learning of invariant representations in the ventral stream, offering both theoretical development and applications.The ventral visual stream is believed to underlie object recognition in primates. Over the past fifty years, researchers have developed a series of quantitative models that are increasingly faithful to the biological architecture. Recently, deep learning convolution networks—which do not reflect several important features of the ventral stream architecture and physiology—have been trained with extremely large datasets, resulting in model neurons that mimic object recognition but do not explain the nature of the computations carried out in the ventral stream. This book develops a mathematical framework that describes learning of invariant representations of the ventral stream and is particularly relevant to deep convolutional learning networks. The authors propose a theory based on the hypothesis that the main computational goal of the ventral stream is to compute neural representations of images that are invariant to transformations commonly encountered in the visual environment and are learned from unsupervised experience. They describe a general theoretical framework of a computational theory of invariance (with details and proofs offered in appendixes) and then review the application of the theory to the feedforward path of the ventral stream in the primate visual cortex.
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Biophysics Of Computation - Information Processing In Single Neurons

by Christof Koch

73,37€ + 10% CARD

 Using experimental and theoretical findings from cellular biophysics, this book explains the computational functions of single neurons. The topics include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; and chemical and electrical synapses and how to treat them from a computational point of view.
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23 Problems In Systems Neuroscience

107,31€ + 10% CARD

 The complexity of the brain and the protean nature of behaviour remain the most elusive area of science, but also the most important. Written by 23 experts from many areas of systems neuroscience, this book provides a useful roadmap to the field of systems neuroscience, and aims to serve as a source of inspiration for explorers of the brain.
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Sensory Cue Integration

102,01€ + 10% CARD

 This book is concerned with sensory cue integration both within and between sensory modalities, and focuses on the emerging way of thinking about cue combination in terms of uncertainty. The probabilistic approaches elaborated in Sensory Cue Integration aim to formalize the uncertainty of cues. They describe cue combination as the nervous system's attempt to minimize uncertainty in its estimates and to choose successful actions.
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Theoretical Neuroscience - Computational And Mathematical Modeling Of Neural Systems

by Laurence F. Abbott e Peter (University College London) Dayan

102,74€ + 10% CARD

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An Introductory Course In Computational Neuroscience

by Paul (Brandeis University) Miller

OUT OF STOCK OR NOT AVAILABLE

 A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior.
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Mechanical Sound - Technology, Culture, And Public Problems Of Noise In Thetwentieth Century

by Karin (Professor Of Science, Technology, And Modern Culture, Maastricht University) Bijsterveld

OUT OF STOCK OR NOT AVAILABLE
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The Computational Brain

by Patricia S. Churchland e Terrence J. (Francis Crick Professor, Salk Institute For Biological Studies) Sejnowski

OUT OF STOCK OR NOT AVAILABLE

 An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists.
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Case Studies In Neural Data Analysis - A Guide For The Practicing Neuroscientist

by Mark A. (Boston University) Kramer e Uri T. (Boston University) Eden

OUT OF STOCK OR NOT AVAILABLE
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Visual Cortex And Deep Networks - Learning Invariant Representations

by Fabio (Massachusetts Institute Of Technology) Anselmi e Tomaso A. (Professor, Massachusetts Institute Of Technology) Poggio

OUT OF STOCK OR NOT AVAILABLE
ENGLISH

Sensory Cue Integration

OUT OF STOCK OR NOT AVAILABLE

 This book is concerned with sensory cue integration both within and between sensory modalities, and focuses on the emerging way of thinking about cue combination in terms of uncertainty. The probabilistic approaches elaborated in Sensory Cue Integration aim to formalize the uncertainty of cues. They describe cue combination as the nervous system's attempt to minimize uncertainty in its estimates and to choose successful actions.
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