The Handbook of Brain Theory and Neural NetworksMichael A. Arbib A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks. 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. |
Contents
How to Use Part I | 3 |
Road Maps A Guided Tour | 25 |
Action Monitoring and Forward Control | 83 |
Adaptive Spike Coding | 90 |
Computational Power | 97 |
AnalogyBased Reasoning and Metaphor | 106 |
Artifical Intelligence and Neural Networks | 113 |
Associative Networks | 117 |
Elementary Mechanisms | 672 |
Motivation | 680 |
Motor Control Biological and Theoretical | 686 |
Motor Pattern Generation | 696 |
Motor Theories of Perception | 705 |
Muscle Models | 711 |
Basic Neuron Types | 719 |
Chemical and Electrical Synapses | 725 |
Auditory Periphery and Cochlear Nucleus | 127 |
Axonal Modeling | 135 |
General Principles | 144 |
Bayesian Methods and Neural Networks | 151 |
Bayesian Networks | 157 |
Biophysical Mechanisms in Neuronal Modeling | 164 |
Biophysical Mosaic of the Neuron | 170 |
BrainComputer Interfaces | 178 |
Cerebellum and Conditioning | 187 |
Neural Plasticity | 196 |
Chaos in Biological Systems | 205 |
Cognitive Development | 212 |
Psychology and Connectionism | 219 |
Collicular Visuomotor Transformations for Gaze | 226 |
Command Neurons and Command Systems | 233 |
Competitive Queuing for Planning and Serial | 241 |
Computing with Attractors | 248 |
Conditioning | 256 |
Consciousness Neural Models of | 263 |
Contour and Surface Perception | 271 |
Cooperative Phenomena | 279 |
Cortical Hebbian Modules | 285 |
Cortical Population Dynamics and Psychophysics | 294 |
Covariance Structural Equation Modeling | 300 |
Data Clustering and Learning | 308 |
Decision Support Systems and Expert Systems | 316 |
Systems | 470 |
Hebbian Learning and Neuronal Regulation | 511 |
Helmholtz Machines and SleepWake Learning | 522 |
Hidden Markov Models | 528 |
Spatial Models | 539 |
Identification and Control | 547 |
Imaging the Motor Brain | 556 |
Imaging the Visual Brain | 562 |
Independent Component Analysis | 569 |
Information Theory and Visual Plasticity | 575 |
Aplysia | 581 |
Neural Implications | 590 |
Language Acquisition | 600 |
The Mirror System Hypothesis | 606 |
Language Processing | 612 |
Theoretical Bounds | 619 |
Learning Network Topology | 628 |
Lesioned Networks as Models of Neuropsychological | 635 |
Localized Versus Distributed Representations | 643 |
Locomotion Vertebrate | 649 |
Markov Random Field Models in Image Processing | 657 |
Model Validation | 666 |
Neuroanatomy in a Computational Perspective | 733 |
Neuroinformatics | 741 |
Neurological and Psychiatric Disorders | 751 |
Neuromodulation in Invertebrate Nervous Systems | 757 |
Neuromorphic VLSI Circuits and Systems | 765 |
Neuropsychological Impairments | 773 |
Synaptic Cellular and Network | 781 |
Object Recognition | 788 |
Object Structure Visual Processing | 797 |
Olfactory Bulb | 806 |
Optimal Sensory Encoding | 815 |
Optimization Neural | 822 |
Orientation Selectivity | 831 |
PAC Learning and Neural Networks | 840 |
Past Tense Learning | 848 |
Pattern Formation Neural | 859 |
Perception of ThreeDimensional Structure | 868 |
Perspective on Neuron Model Complexity | 877 |
Philosophical Issues in Brain Theory | 886 |
Population Codes | 893 |
Potential Fields and Neural Networks | 901 |
Principal Component Analysis | 910 |
Programmable Neurocomputing Systems | 916 |
Prosthetics Neural | 923 |
Pursuit Eye Movements | 929 |
Radial Basis Function Networks | 937 |
Implications for Computational | 945 |
Reading | 951 |
Neurophysiological Modeling | 960 |
Reinforcement Learning in Motor Control | 968 |
Retina | 975 |
Robot Learning | 983 |
Rodent Head Direction System | 990 |
Scratch Reflex | 999 |
SelfOrganizing Feature Maps | 1005 |
Sensor Fusion | 1014 |
Sensorimotor Learning | 1020 |
Sequence Learning | 1027 |
Silicon Neurons | 1034 |
SingleCell Models | 1044 |
Somatosensory System | 1053 |
Sound Localization and Binaural Processing | 1061 |
Psycholinguistics | 1068 |
Statistical Mechanics of Generalization | 1087 |
Editorial Advisory Board | 1239 |
| 1255 | |
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The Handbook of Brain Theory and Neural Networks Edited By Michael A. Arbib No preview available - 2006 |