Foundations and Tools for Neural Modeling

Table of Contents

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   Book Overview
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   Chapter 1 Self-assembly of oscillatory neurons and networks
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   Chapter 2 Reverberating loops of information as a dynamic mode of functional organization of the N. S.: A working conjecture
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   Chapter 3 Reconstruction of brain networks by algorithmic amplification of morphometry data
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   Chapter 4 Slow learning and fast evolution: An approach to cytoarchitectonic parcellation
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   Chapter 5 Dendritic [Ca2+] dynamics in the presence of immobile buffers and of dyes
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   Chapter 6 Development of directionally selective microcircuits in striate cortex
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   Chapter 7 Neural circuitry and plasticity in the adult vertebrate inner retina
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   Chapter 8 Modelling the circuitry of the cuneate nucleus
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    Chapter 9 Filtering capability of neural networks from the developing mammalian hippocampus
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    Chapter 10 Spatial inversion and facilitation in the J. Gonzalo’s research of the sensorial cortex. Integrative aspects
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    Chapter 11 A self-organizing model for the development of ocular dominance and orientation columns in the visual cortex
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    Chapter 12 Gaze control with neural networks: A unified approach for saccades and smooth pursuit
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    Chapter 13 The neural net of Hydra and the modulation of its periodic activity
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    Chapter 14 A biophysical model of intestinal motility: Application in pharmacological studies
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    Chapter 15 Model of the neuronal net for detection of single bars and cross-like figures
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    Chapter 16 Connected cortical recurrent networks
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    Chapter 17 Inter-spike interval statistics of cortical neurons
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    Chapter 18 A new cochlear model based on adaptive gain mechanism
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    Chapter 19 Structure of lateral inhibition in an olfactory bulb model
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    Chapter 20 Effects of correlation and degree of balance in random synaptic inputs on the output of the hodgkin-huxley model
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    Chapter 21 Oscillations in the lower stations of the somatosensory pathway
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    Chapter 22 Effects of the ganglion cell response nonlinear mapping on visual system’s noise filtering characteristics
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    Chapter 23 Paradoxical relationship between output and input regularity for the FitzHugh-Nagumo model
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    Chapter 24 Synchronisation in a network of FHN units with synaptic-like coupling
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    Chapter 25 Two-compartment stochastic model of a neuron with periodic input
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    Chapter 26 Stochastic model of the place cell discharge
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    Chapter 27 Integrate-and-fire model with correlated inputs
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    Chapter 28 Noise modulation by stochastic neurons of the integrate-and fire type
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    Chapter 29 Bayesian modelling of neural networks
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    Chapter 30 Neural networks of the hopfield type
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    Chapter 31 Stability properties of BSB models
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    Chapter 32 Storage capacity of the exponential correlation associative memory
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    Chapter 33 A new input-output function for binary hopfield neural networks
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    Chapter 34 On the three layer neural networks using sigmoidal functions
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    Chapter 35 The capacity and attractor basins of associative memory models
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    Chapter 36 A modular attractor model of semantic access
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    Chapter 37 Priming an artificial associative memory
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    Chapter 38 What does a peak in the landscape of a Hopfield associative memory look like?
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    Chapter 39 Periodic and synchronic firing in an ensemble of identical stochastic units: Structural stability
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    Chapter 40 Driving neuromodules into synchronous chaos
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    Chapter 41 Aging and lévy distributions in sandpiles
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    Chapter 42 Finite size effects in neural networks
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    Chapter 43 On the computational power of limited precision weights neural networks in classification problems: How to calculate the weight range so that a solution will exist
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    Chapter 44 Estimating exact form of generalisation errors
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    Chapter 45 A network model for the emergence of orientation maps and local lateral circuits
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    Chapter 46 A neural network model for the self-organization of cortical grating cells
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    Chapter 47 Extended nonlinear hebbian learning for developing sparse-distributed representation
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    Chapter 48 Cascade error projection: A learning algorithm for hardware implementation
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    Chapter 49 Unification of supervised and unsupervised training
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    Chapter 50 On-line optimization of radial basis function networks with orthogonal techniques
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    Chapter 51 A fast orthogonalized FIR adaptive filter structure using recurrent hopfield-like network
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    Chapter 52 Using temporal neighborhoods to adapt function approximators in reinforcement learning
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    Chapter 53 Autonomous clustering for machine learning
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    Chapter 54 Bioinspired framework for general-purpose learning
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    Chapter 55 Learning efficient rulesets from fuzzy data with a genetic algorithm
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    Chapter 56 Self-organizing cases to find paradigms
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    Chapter 57 Training higher order Gaussian synapses
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    Chapter 58 On-line gradient learning algorithms for K-nearest neighbor classifiers
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    Chapter 59 Structure adaptation in artificial neural networks through adaptive clustering and through growth in state space
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    Chapter 60 Sensitivity analysis of radial basis function networks for fault tolerance purposes
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    Chapter 61 Association with multi-dendritic radial basis units
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    Chapter 62 Foundations and Tools for Neural Modeling
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    Chapter 63 SOAN: Self organizing with adaptive neighborhood neural network
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    Chapter 64 Topology preservation in SOFM: An euclidean versus manhattan distance comparison
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    Chapter 65 Supervised VQ learning based on temporal inhibition
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    Chapter 66 Improving the LBG algorithm
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    Chapter 67 Sequential learning algorithm for PG-RBF network using regression weights for time series prediction
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    Chapter 68 Parallel fuzzy learning
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    Chapter 69 Classification and feature selection by a self-organizing neural network
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    Chapter 70 SA-prop: Optimization of multilayer perceptron parameters using simulated annealing
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    Chapter 71 Mobile robot path planning using genetic algorithms
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    Chapter 72 Do plants optimize?
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    Chapter 73 Heuristic generation of the initial population in solving job shop problems by evolutionary strategies
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    Chapter 74 Randomness in heuristics: An experimental investigation for the maximum satisfiability problem
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    Chapter 75 Solving the packing and strip-packing problems with genetic algorithms
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    Chapter 76 Multichannel pattern recognition neural network
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    Chapter 77 A biologically plausible maturation of an ART network
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    Chapter 78 Adaptive resonance theory microchips
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    Chapter 79 Application of ART2-A as a pseudo-supervised paradigm to nuclear reactor diagnostics
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    Chapter 80 Supervised ART-I: A new neural network architecture for learning and classifying multi-valued input patterns
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    Chapter 81 Conscious and intentional access to unconscious decision-making module in ambiguous visual perception
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    Chapter 82 A psychophysical approach to the mechanism of human stereovision
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    Chapter 83 Neuronal coding and color sensations
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    Chapter 84 Neurocomputational models of visualisation: A preliminary report
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    Chapter 85 Self-organization of shift-invariant receptive fields
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    Chapter 86 Pattern recognition system with top-down process of mental rotation
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    Chapter 87 Segmentation of occluded objects using a hybrid of selective attention and symbolic knowledge
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    Chapter 88 Hypercolumn model: A modified model of neocognitron using hierarchical self-organizing maps
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    Chapter 89 Attentional strategies for object recognition