Computational Neuroscience

Computational Neuroscience : Trends in Research

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Description

This volume represents the diverse but interrelated nature of computational neuroscience research. The chapters are grouped into four different levels of investigation and analysis: subcellular, cellular, network and systems. This organization allows for a non-traditional view of the literature which is typically grouped by lines of experimental subject or subsystem studied. The book focuses on the computational questions and approaches characteristic of each level of analysis.
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Product details

  • Hardback | 650 pages
  • 152 x 229 x 27mm | 894g
  • Academic Press Inc
  • San Diego, United States
  • English
  • b&w illustrations
  • 0121210405
  • 9780121210403

About James M. Bower

Edited by James M. Bower
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Table of contents

Subcellular: Channel model of second messenger mediated transformation of GABA induced currents, K.T. Blackwell et al; Modelling the spontaneous release of Quantal at active zones of varicosities Boutons and endplates, W.G. Gibson et al; Simulation of Quantal transmission at purinergic junctions, W.G. Gibson et al; A covariance-based learning rule for the hippocampus, T.S. Green, A.A. Minai; Hebbian learning weight normalization, and the development of segregates, A. Harris et al; Novel expression mechanisms for short-term potentiation: experimental and modelling studies, X. Xie et al. Cellular: The concept of decision points as a tool in analyzing dendritic computation, H. Agman-Snir, I. Segev; Plateau potentials in bistables mononeurons, V. Booth, J. Rinzel; Computentional models constrained by voltage-clamp data for investigating dendritic currents, A. Destexhe et al; Characterization of synfire activity by propagating "pulse packets", M. Diesmann et al; Electrical properties of subthalamic nucleus projection neurons, A.J. Gillies; Modelling the inhibition of la impute in Cat-a-motoneurons based on morphological and physiological data, G. Gragwahl et al; Computer simulation of mechanisms for unblocking axons, B.P. Graham; Modelling the effects of ambient glutamate on NMDA and non-NMDA conductances, W.R. Holmes; Relationship between morphological and electrophysiological properties of dopaminergic neurons, R. Koller, M. Feizelmeier; On the role of dendritic inhibition in associative LTP, W.B. Levy et al; A biologically-plausible model of neurons in the cochlear nucleus that computes accurate spike times for complex stimuli in real-time, K.L. Levy et al; Estimation of membrane properties from step current measurements of xenopus neurons, C.R. Murphey et al; Stochastic resonance and noise in the neural coding of sensory signals, B.R. Parnas; Activation of the fast sodium conductance in pyramidal cells by temporal patterns of geniculocortical synapses, A.J. Peiper, P.S. Ulinski; Stochastic intensity of neural spike discharge based on active channel dynamics, R.M. Schmich, M.I. Miller; Neural decoding and synaptic responses prediction, K. Sen et al; Non-classical receptive fields and the role of lateral connections in primary visual cortex: from physiology to psychophysics, M. Stemmler et al; Coding of inhibitory transients: comparison of model and living preparation, M. Stiber et al; Do neurons in the barn owl couple to extracellular potentials? C.D. Spence, J.C. Pearson. (Part contents).
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