The handbook of brain theory and neural networks /

The handbook of brain theory and neural networks /

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Bibliographic Details
Edition:2nd ed.
Imprint:Cambridge, Mass. : MIT Press, c2003.
Description:xvii, 1290 p. : ill. ; 29 cm.
Language:English
Subject:
Neural networks (Neurobiology) -- Handbooks, manuals, etc.
Neural networks (Computer science) -- Handbooks, manuals, etc.
Neural networks (Computer science)
Neural networks (Neurobiology)
Handbooks and manuals.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/4785279
Hidden Bibliographic Details
Varying Form of Title:Brain theory and neural networks
Other authors / contributors:Arbib, Michael A.
ISBN:0262011972
Notes:Includes bibliographical references and index.

MARC

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245 0 4 |a The handbook of brain theory and neural networks /  |c edited by Michael A. Arbib ; editoral advisory board, Shun-Ichi Amari ... [et al.] ; editoral assistant, Prudence H. Arbib. 
246 3 0 |a Brain theory and neural networks 
250 |a 2nd ed. 
260 |a Cambridge, Mass. :  |b MIT Press,  |c c2003. 
300 |a xvii, 1290 p. :  |b ill. ;  |c 29 cm. 
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504 |a Includes bibliographical references and index. 
505 0 0 |g Pt. I.  |t Background: The Elements of Brain Theory and Neural Networks --  |t Introducing the Neuron --  |t Levels and Styles of Analysis --  |t Dynamics and Adaptation in Neural Networks --  |g Pt. II.  |t Road Maps: A Guided Tour of Brain Theory and Neural Networks --  |t The Meta-Map --  |t Grounding Models of Neurons and Networks --  |t Brain, Behavior, and Cognition --  |t Psychology, Linguistics, and Artificial Intelligence --  |t Biological Neurons and Networks --  |t Dynamics and Learning in Artificial Networks --  |t Sensory Systems --  |t Motor Systems --  |t Applications, Implementations, and Analysis --  |g Pt. III.  |t Articles --  |t Action Monitoring and Forward Control of Movements --  |t Activity-Dependent Regulation of Neuronal Conductances --  |t Adaptive Resonance Theory --  |t Adaptive Spike Coding --  |t Amplification, Attenuation, and Integration --  |t Analog Neural Nets: Computational Power --  |t Analog VLSI Implementations of Neural Networks --  |t Analogy-Based Reasoning and Metaphor --  |t Arm and Hand Movement Control --  |t Artificial Intelligence and Neural Networks --  |t Associative Networks --  |t Auditory Cortex --  |t Auditory Periphery and Cochlear Nucleus --  |t Auditory Scene Analysis --  |t Axonal Modeling --  |t Axonal Path Finding --  |t Backpropagation: General Principles --  |t Basal Ganglia --  |t Bayesian Methods and Neural Networks --  |t Bayesian Networks --  |t Biologically Inspired Robotics --  |t Biophysical Mechanisms of Neuronal Modeling --  |t Biophysical Mosaic of the Neuron --  |t Brain Signal Analysis --  |t Brain-Computer Interfaces --  |t Canonical Neural Models --  |t Cerebellum and Conditioning --  |t Cerebellum and Motor Control --  |t Cerebellum: Neural Plasticity --  |t Chains of Oscillators in Motor and Sensory Systems --  |t Chaos in Biological Systems --  |t Chaos in Neural Systems --  |t Cognitive Development --  |t Cognitive Maps --  |t Cognitive Modeling: Psychology and Connectionism --  |t Collective Behavior of Coupled Oscillators --  |t Collicular Visuomotor Transformations for Gaze Control --  |t Color Perception --  |t Command Neurons and Command Systems --  |t Competitive Learning --  |t Competitive Queuing for Planning and Serial Performance --  |t Compositionality in Neural Systems --  |t Computing with Attractors --  |t Concept Learning --  |t Conditioning --  |t Connectionist and Symbolic Representations --  |t Consciousness, Neural Models of --  |t Constituency and Recursion in Language --  |t Contour and Surface Perception --  |t Convolutional Networks for Images, Speech, and Time Series --  |t Cooperative Phenomena --  |t Cortical Hebbian Modules --  |t Cortical Memory --  |t Cortical Population Dynamics and Psychophysics --  |t Covariance Structural Equation Modeling --  |t Crustacean Stomatogastric System --  |t Data Clustering and Learning --  |t Databases for Neuroscience --  |t Decision Support Systems and Expert Systems --  |t Dendritic Learning --  |t Dendritic Processing --  |t Dendritic Spines --  |t Development of Retinotectal Maps --  |t Developmental Disorders --  |t Diffusion Models of Neuron Activity --  |t Digital VLSI for Neural Networks --  |t Directional Selectivity --  |t Dissociations Between Visual Processing Modes --  |t Dopamine, Roles of --  |t Dynamic Link Architecture --  |t Dynamic Remapping --  |t Dynamics of Bifurcation in Neural Nets --  |t Dynamics of Association and Recall --  |t Echolocation: Cochleotopic and Computational Maps --  |t EEG and MEG Analysis --  |t Electrolocation --  |t Embodied Cognition --  |t Emotional Circuits --  |t Energy Functionals for Neural Networks --  |t Ensemble Learning --  |t Equilibrium Point Hypothesis --  |t Event-Related Potentials --  |t Evolution and Learning in Neural Networks --  |t Evolution of Artificial Neural Networks --  |t Evolution of Genetic Networks --  |t Evolution of the Ancestral Vertebrate Brain --  |t Eye-Hand Coordination in Reaching Movements --  |t Face Recognition: Neurophysiology and Neural Technology --  |t Face Recognition: Psychology and Connectionism --  |t Fast Visual Processing --  |t Feature Analysis --  |t Filtering, Adaptive --  |t Forecasting --  |t Gabor Wavelets and Statistical Pattern Recognition --  |t Gait Transitions --  |t Gaussian Processes --  |t Generalization and Regularization in Nonlinear Learning Systems --  |t GENESIS Simulation System --  |t Geometrical Principles in Motor Control --  |t Global Visual Pattern Extraction --  |t Graphical Models: Parameter Learning --  |t Graphical Models: Probabilistic Inference --  |t Graphical Models: Structure Learning --  |t Grasping Movements: Visuomotor Transformations --  |t Habituation --  |t Half-Center Oscillators Underlying Rhythmic Movements --  |t Hebbian Learning and Neuronal Regulation --  |t Hebbian Synaptic Plasticity --  |t Helmholtz Machines and Sleep-Wake Learning --  |t Hemispheric Interactions and Specialization --  |t Hidden Markov Models --  |t Hippocampal Rhythm Generation --  |t Hippocampus: Spatial Models --  |t Hybrid Connectionist/Symbolic Systems --  |t Identification and Control --  |t Imaging the Grammatical Brain --  |t Imaging the Motor Brain --  |t Imaging the Visual Brain --  |t Imitation --  |t Independent Component Analysis --  |t Information Theory and Visual Plasticity --  |t Integrate-and-Fire Neurons and Networks --  |t Invertebrate Models of Learning: Aplysia and Hermissenda --  |t Ion Channels: Keys to Neuronal Specialization --  |t Kalman Filtering: Neural Implications --  |t Laminar Cortical Architecture in Visual Perception --  |t Language Acquisition --  |t Language Evolution and Change --  |t Language Evolution: The Mirror System Hypothesis --  |t Language Processing --  |t Layered Computation in Neural Networks --  |t Learning and Generalization: Theoretical Bounds --  |t Learning and Statistical Inference --  |t Learning Network Topology --  |t Learning Vector Quantization --  |t Lesioned Networks as Models of Neuropsychological Deficits --  |t Limb Geometry, Neural Control --  |t Localized Versus Distributed Representations --  |t Locomotion, Invertebrate --  |t Locomotion, Vertebrate --  |t Locust Flight: Components and Mechanisms in the Motor --  |t Markov Random Field Models in Image Processing --  |t Memory-Based Reasoning --  |t Minimum Description Length Analysis --  |t Model Validation --  |t Modular and Hierarchical Learning Systems --  |t Motion Perception: Elementary Mechanisms --  |t Motion Perception: Navigation --  |t Motivation --  |t Motoneuron Recruitment --  |t Motor Control, Biological and Theoretical --  |t Motor Cortex: Coding and Decoding of Directional Operations --  |t Motor Pattern Generation --  |t Motor Primitives --  |t Motor Theories of Perception --  |t Multiagent Systems --  |t Muscle Models --  |t Neocognitron: A Model for Visual Pattern Recognition --  |t Neocortex: Basic Neuron Types --  |t Neocortex: Chemical and Electrical Synapses --  |t Neural Automata and Analog Computational Complexity --  |t Neuroanatomy in a Computational Perspective --  |t Neuroethology, Computational --  |t Neuroinformatics --  |t Neurolinguistics --  |t Neurological and Psychiatric Disorders --  |t Neuromanifolds and Information Geometry --  |t Neuromodulation in Invertebrate Nervous Systems --  |t Neuromodulation in Mammalian Nervous Systems --  |t Neuromorphic VLSI Circuits and Systems --  |t NEURON Simulation Environment --  |t Neuropsychological Impairments --  |t Neurosimulation: Tools and Resources --  |t NMDA Receptors: Synaptic, Cellular, and Network Models --  |t NSL Neural Simulation Language --  |t Object Recognition --  |t Object Recognition, Neurophysiology --  |t Object Structure, Visual Processing --  |t Ocular Dominance and Orientation Columns --  |t Olfactory Bulb --  |t Olfactory Cortex --  |t Optimal Sensory Encoding --  |t Optimality Theory in Linguistics --  |t Optimization, Neural --  |t Optimization Principles in Motor Control --  |t Orientation Selectivity --  |t Oscillatory and Bursting Properties of Neurons --  |t PAC Learning and Neural Networks --  |t Pain Networks --  |t Past Tense Learning --  |t Pattern Formation, Biological --  |t Pattern Formation, Neural --  |t Pattern Recognition --  |t Perception of Three-Dimensional Structure --  |t Perceptrons, Adalines, and Backpropagation --  |t Perspective on Neuron Model Complexity --  |t Phase-Plane Analysis of Neural Nets --  |t Philosophical Issues in Brain Theory and Connectionism --  |t Photonic Implementations of Neurobiologically Inspired Networks --  |t Population Codes -- 
505 8 0 |t Post-Hebbian Learning Algorithms --  |t Potential Fields and Neural Networks --  |t Prefrontal Cortex in Temporal Organization of Action --  |t Principal Component Analysis --  |t Probabilistic Regularization Methods for Low-Level Vision --  |t Programmable Neurocomputing Systems --  |t Prosthetics, Motor Control --  |t Prosthetics, Neural --  |t Prosthetics, Sensory Systems --  |t Pursuit Eye Movements --  |t Q-Learning for Robots --  |t Radial Basis Function Networks --  |t Rate Coding and Signal Processing --  |t Reaching Movements: Implications for Computational Models --  |t Reactive Robotic Systems --  |t Reading --  |t Recurrent Networks: Learning Algorithms --  |t Recurrent Networks: Neurophysiological Modeling --  |t Reinforcement Learning --  |t Reinforcement Learning in Motor Control --  |t Respiratory Rhythm Generation --  |t Retina --  |t Robot Arm Control --  |t Robot Learning --  |t Robot Navigation --  |t Rodent Head Direction System --  |t Schema Theory --  |t Scratch Reflex --  |t Self-Organization and the Brain --  |t Self-Organizing Feature Maps --  |t Semantic Networks --  |t Sensor Fusion --  |t Sensorimotor Interactions and Central Pattern Generators --  |t Sensorimotor Learning --  |t Sensory Coding and Information Transmission --  |t Sequence Learning --  |t Short-Term Memory --  |t Silicon Neurons --  |t Simulated Annealing and Boltzmann Machines --  |t Single-Cell Models --  |t Sleep Oscillations --  |t Somatosensory System --  |t Somatotopy: Plasticity of Sensory Maps --  |t Sound Localization and Binaural Processing --  |t Sparse Coding in the Primate Cortex --  |t Speech Processing: Psycholinguistics --  |t Speech Production --  |t Speech Recognition Technology --  |t Spiking Neurons, Computation with --  |t Spinal Cord of Lamprey: Generation of Locomotor Patterns --  |t Statistical Mechanics of Generalization --  |t Statistical Mechanics of Neural Networks --  |t Statistical Mechanics of On-line Learning and Generalization --  |t Statistical Parametric Mapping of Cortical Activity Patterns --  |t Stereo Correspondence --  |t Stochastic Approximation and Efficient Learning --  |t Stochastic Resonance --  |t Structured Connectionist Models --  |t Support Vector Machines --  |t Synaptic Interactions --  |t Synaptic Noise and Chaos in Vertebrate Neurons --  |t Synaptic Transmission --  |t Synchronization, Binding and Expectancy --  |t Synfire Chains --  |t Synthetic Functional Brain Mapping --  |t Systematicity and Generalizations in Connectionist Networks --  |t Temporal Dynamics of Biological Synapses --  |t Temporal Integration in Recurrent Microcircuits --  |t Temporal Pattern Processing --  |t Temporal Sequences: Learning and Global Analysis --  |t Tensor Voting and Visual Segmentation --  |t Thalamus --  |t Universal Approximators --  |t Unsupervised Learning with Global Objective Functions --  |t Vapnik-Chervonenkis Dimension of Neural Networks --  |t Vestibulo-Ocular Reflex --  |t Visual Attention --  |t Visual Cortex: Anatomical Structure and Models of Function --  |t Visual Course Control in Flies --  |t Visual Scene Perception, Neurophysiology --  |t Visual Scene Segmentation --  |t Visuomotor Coordination in Frog and Toad --  |t Visuomotor Coordination in Salamander --  |t Winner-Take-All Networks --  |t Ying-Yang Learning. 
650 0 |a Neural networks (Neurobiology)  |v Handbooks, manuals, etc. 
650 0 |a Neural networks (Computer science)  |v Handbooks, manuals, etc. 
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927 |t Library of Congress classification  |a QP363.3 .H36 2003  |l JCL  |c JCL-Sci  |e MARO  |e CRERAR  |b 63283601  |i 7381474 
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