Download the dynamic neuron bradford books in pdf or read the dynamic neuron bradford books in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get the dynamic neuron bradford books in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



The Dynamic Neuron

Author: John Smythies
Publisher: MIT Press
ISBN: 9780262264679
Size: 33.41 MB
Format: PDF
View: 2858
Download and Read
A comprehensive review of current research on synaptic plasticity. The traditional model of synapses as fixed structures has been replaced by a dynamic one in which synapses are constantly being deleted and replaced. This book, written by a leading researcher on the neurochemistry of schizophrenia, integrates material from neuroscience and cell biology to provide a comprehensive account of our current knowledge of the neurochemical basis of synaptic plasticity. The book presents the evidence for synaptic plasticity, an account of the dendritic spine and the glutamate synapse with a focus on redox mechanisms, and the biochemical basis of the Hebbian synapse. It discusses the role of endocytosis, special proteins, and local protein synthesis. Additional topics include volume transmission, arachidonic acid signaling, hormonal modulation, and psychological stress. Finally, the book considers pharmacological and clinical implications of current research, particularly with reference to schizophrenia and Alzheimer's disease.

The Neurobiology Of Neural Networks

Author: Daniel Gardner
Publisher: MIT Press
ISBN: 9780262071505
Size: 80.56 MB
Format: PDF, Docs
View: 4527
Download and Read
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.Daniel Gardner is Professor of Physiology and Biophysics at Cornell University Medical College.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.

The Handbook Of Brain Theory And Neural Networks

Author: Michael A. Arbib
Publisher: MIT Press
ISBN: 0262011972
Size: 25.20 MB
Format: PDF, ePub, Mobi
View: 876
Download and Read
This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions: how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Advances In Neural Information Processing Systems 8

Author: David S. Touretzky
Publisher: MIT Press
ISBN: 9780262201070
Size: 42.84 MB
Format: PDF, Docs
View: 5295
Download and Read
The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control. Chapters describe how neuroscientists and cognitive scientists use computational models of neural systems to test hypotheses and generate predictions to guide their work. This work includes models of how networks in the owl brainstem could be trained for complex localization function, how cellular activity may underlie rat navigation, how cholinergic modulation may regulate cortical reorganization, and how damage to parietal cortex may result in neglect. Additional work concerns development of theoretical techniques important for understanding the dynamics of neural systems, including formation of cortical maps, analysis of recurrent networks, and analysis of self- supervised learning. Chapters also describe how engineers and computer scientists have approached problems of pattern recognition or speech recognition using computational architectures inspired by the interaction of populations of neurons within the brain. Examples are new neural network models that have been applied to classical problems, including handwritten character recognition and object recognition, and exciting new work that focuses on building electronic hardware modeled after neural systems. A Bradford Book

Methods In Neuronal Modeling

Author: Christof Koch
Publisher: MIT Press
ISBN: 9780262112314
Size: 10.93 MB
Format: PDF, Mobi
View: 2887
Download and Read
This book serves as a handbook of computational methods and techniques for modeling the functional properties of single and groups of nerve cells.

From Animals To Animats 7

Author: Bridget Hallam
Publisher: MIT Press
ISBN: 9780262582179
Size: 60.40 MB
Format: PDF
View: 3933
Download and Read
Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior The Simulation of Adaptive Behavior Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, computer science, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow adaptation and survival in uncertain environments. The work presented focuses on robotic and computational experimentation with well-defined models that help to characterize and compare alternative organizational principles or architectures underlying adaptive behavior in both natural animals and synthetic animats.

Neural Organization

Author: Michael A. Arbib
Publisher: MIT Press
ISBN: 9780262011594
Size: 54.90 MB
Format: PDF, Docs
View: 5829
Download and Read
In "Neural Organization," Arbib, É rdi, and Szentá gothai integrate structural, functional, and dynamical approaches to the interaction of brain models and neurobiologcal experiments. Both structure-based "bottom-up" and function- based "top-down" models offer coherent concepts by which to evaluate the experimental data. The goal of this book is to point out the advantages of a multidisciplinary, multistrategied approach to the brain. Part I of "Neural Organization" provides a detailed introduction to each of the three areas of structure, function, and dynamics. "Structure" refers to the anatomical aspects of the brain and the relations between different brain regions. "Function" refers to skills and behaviors, which are explained by means of functional schemas and biologically based neural networks. "Dynamics" refers to the use of a mathematical framework to analyze the temporal change of neural activities and synaptic connectivities that underlie brain development and plasticity--in terms of both detailed single-cell models and large-scale network models. In part II, the authors show how their systematic approach can be used to analyze specific parts of the nervous system--the olfactory system, hippocampus, thalamus, cerebral cortex, cerebellum, and basal ganglia--as well as to integrate data from the study of brain regions, functional models, and the dynamics of neural networks. In conclusion, they offer a plan for the use of their methods in the development of cognitive neuroscience.

Advances In Neural Information Processing Systems 8

Author: David S. Touretzky
Publisher: MIT Press
ISBN: 9780262201070
Size: 80.35 MB
Format: PDF, ePub, Mobi
View: 1590
Download and Read
The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control. Chapters describe how neuroscientists and cognitive scientists use computational models of neural systems to test hypotheses and generate predictions to guide their work. This work includes models of how networks in the owl brainstem could be trained for complex localization function, how cellular activity may underlie rat navigation, how cholinergic modulation may regulate cortical reorganization, and how damage to parietal cortex may result in neglect. Additional work concerns development of theoretical techniques important for understanding the dynamics of neural systems, including formation of cortical maps, analysis of recurrent networks, and analysis of self- supervised learning. Chapters also describe how engineers and computer scientists have approached problems of pattern recognition or speech recognition using computational architectures inspired by the interaction of populations of neurons within the brain. Examples are new neural network models that have been applied to classical problems, including handwritten character recognition and object recognition, and exciting new work that focuses on building electronic hardware modeled after neural systems. A Bradford Book

A Dynamic Systems Approach To The Development Of Cognition And Action

Author: Esther Thelen
Publisher: MIT Press
ISBN: 9780262700597
Size: 78.54 MB
Format: PDF, ePub, Docs
View: 5125
Download and Read
"A radical departure from most of current cognitive development theory.... Nativists, structuralists, empiricists and social constructivists will disagree with different parts of this book. Yet this landmark volume is essential reading for all of them." -- Annette Karmiloff-Smith and Mark H. Johnson, "Nature" A Dynamic Systems Approach to the Development of Cognition and Action presents a comprehensive and detailed theory of early human development based on the principles of dynamic systems theory. Beginning with their own research in motor, perceptual, and cognitive development, Thelen and Smith raise fundamental questions about prevailing assumptions in the field. They propose a new theory of the development of cognition and action, unifying recent advances in dynamic systems theory with current research in neuroscience and neural development. In particular, they show how by processes of exploration and selection, multimodal experiences form the bases for self-organizing perception-action categories. Thelen and Smith offer a radical alternative to current cognitive theory, both in their emphasis on dynamic representation and in their focus on processes of change. Among the first attempt to apply complexity theory to psychology, they suggest reinterpretations of several classic issues in early cognitive development. The book is divided into three sections. The first discusses the nature of developmental processes in general terms, the second covers dynamic principles in process and mechanism, and the third looks at how a dynamic theory can be applied to enduring puzzles of development. Cognitive Psychology series

Evolvable Systems From Biology To Hardware

Author: Andy M. Tyrrell
Publisher: Springer
ISBN: 3540365532
Size: 72.90 MB
Format: PDF
View: 4850
Download and Read
The idea of evolving machines, whose origins can be traced to the cybernetics movementofthe1940sand1950s,hasrecentlyresurgedintheformofthenascent ?eld of bio-inspired systems and evolvable hardware. The inaugural workshop, Towards Evolvable Hardware, took place in Lausanne in October 1995, followed by the First International Conference on Evolvable Systems: From Biology to Hardware (ICES), held in Tsukuba, Japan in October 1996. The second ICES conference was held in Lausanne in September 1998, with the third and fourth being held in Edinburgh, April 2000 and Tokyo, October 2001 respectively. This has become the leading conference in the ?eld of evolvable systems and the 2003 conference promised to be at least as good as, if not better than, the four that preceeded it. The ?fth international conference was built on the success of its predec- sors, aiming at presenting the latest developments in the ?eld. In addition, it brought together researchers who use biologically inspired concepts to imp- ment real systems in arti?cial intelligence, arti?cial life, robotics, VLSI design and related domains. We would say that this ?fth conference followed on from the previous four in that it consisted of a number of high-quality interesting thought-provoking papers.