The Handbook of Brain Theory and Neural Networks
Michael A. Arbib
MIT Press, 2003 - Computers - 1290 pages
Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks 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?Once again, the heart of the book is a set of almost 300 articles covering the whole spectrum of topics in brain theory and neural networks. The first two parts of the book, prepared by Michael Arbib, are designed to help readers orient themselves in this wealth of material. Part I provides general background on brain modeling and on both biological and artificial neural networks. Part II consists of "Road Maps" to help readers steer through articles in part III on specific topics of interest. The articles in part III are written so as to be accessible to readers of diverse backgrounds. They are cross-referenced and provide lists of pointers to Road Maps, background material, and related reading.The second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. It contains 287 articles, compared to the 266 in the first edition. Articles on topics from the first edition have been updated by the original authors or written anew by new authors, and there are 106 articles on new topics.
What people are saying - Write a review
This book, though outdated, treats with some great, interesting concepts, like Dynamic link architecture. This is the formation of a set of dynamic linked nodes to create objects in human memory, like a dynamic link library, but for the human brain.
At 1290 pages, the name "handbook" hardly applies, but the book would help anyone studying psychology, memory, learning, or even specialized fields like heart medicine.
From Computer to Brain: Foundations of Computational Neuroscience
William W. Lytton
Limited preview - 2002
How to Use Part l
Road Maps A GuIded Tour
Action Monitoring and Forward Control
Adaptive Spike Coding
AnalogyBased Reasoning and Metaphor
Artifical lntelligence and Neural Networks
Motor Control Biological and Theoretical
Motor Paneru Generation
Motor Theories ot Perception
Basic Neuron Types
Chemical and Electrical Synapses
Neuroanatomy in a Computational Perspective
Auditory Periphery and Cochiear Nacleus
Bayesian Methods and Neural Networks
Biophysical Mechanisms in Neuronal Modeling
Biophysical Mosaic of the Neuron
Cerebellam and Conditioning
Chaos in Biological Systems
Psychology and Connectionism
Collicular Visuomotor Transformations for Gaze
Command Neurons and Command Systems
Competitive Queuing for Planning and Serial
Computing with Anractors
Consciousness Neural Models of
Contour and Surface Perception
Cortical Hebbian Modules
Cortical Population Dynamics and Psychophysics
Crustacean SIomaIogasIric System
Databases for Neuroscience
Hcbbian Synuptie Plastieity
Hidden Markov Models
1dentification and Control
lmaging the Motor Brain
lmaging the Visual Bratn
lndependent Component Analysis
1nformation Theory and Visual Plasticity
The Mirror System Hypothesis
Learuing Network Topology
Lesioned Networks as Models of Neuropsychological
Localized Versus Distributed Representations
Markov Random Field Models in image Processing
Neurological and Psychiatric Disorders
Neuromodulation in lnvertebrate Nervous Systems
Neuromorphic VLSl Circuits and Systems
Tools and Resources
NSL Neural Simulation Language
Object Recognition Neurophysiology
Ocular Dominance and Orientation Colamns
Optimally Theory in Linguistics
Optimization Principles in Motor Control
Oscillatory and Bursting Properties of Neurons
Paneru Formation Biological
Paneru Formation Neural
Perception of TbreeDimensional Structure
Perspective on Neuron Model Complexity
Philosophical lssues in Brain Theory
Potential Fields and Neural Networks
Principal Component Analysis
Programmable Neurocomputing Systems
Parsuit Eye Movements
Radial Basis Function Networks
1mplications for Computational
Reinforcement Learuing in Motor Control
Rodent Head Direction System
SelfOrganizing Feature Maps
Sound Localization and Binaural Processing
Editorial Advisory Board
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The Handbook of Brain Theory and Neural Networks - The MIT Press
A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks
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