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• LDR

  01999nam a22003734c 4500

• 001

  000000785334

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  20151119153414

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  090929s2010 ne a b 001 0 eng d

• 020

  ▼a  9780123748829

• 020

  ▼a  0123748828

• 040

  ▼a  243002

• 041

  ▼a  eng

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  ▼a  nlmcopyc

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  ▼a  Gabbiani, Fabrizio.

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  ▼a  Mathematics for neuroscientists /
  ▼d  Fabrizio Gabbiani ;
  ▼e  Steven J. Cox.

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  ▼a  1st ed.

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  ▼a  Amsterdam:
  ▼b  Elsevier/Academic Press,
  ▼c  2010.

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  ▼a  xi, 486 p.:
  ▼b  ill. (some col.);
  ▼c  28 cm.

• 504

  ▼a  Includes bibliographical references (p. 473-482) and index.

• 505

  ▼a  Passive isopotential cell -- Differential equations -- Active isopotential cell -- Quasi-active isopotential cell -- Passive cable -- Fourier series and transforms -- Passive dendritic tree -- Active dendritic tree -- Reduced single neuron models -- Probability and random variables -- Synaptic transmission and quantal release -- Neuronal calcium signaling -- Singular value decomposition and applications -- Quantification of spike train variability -- Stochastic processes -- Membrane noise -- Power and cross spectra -- Natural light signals and phototransduction -- Firing rate codes and early vision -- Models of simple and complex cells -- Stochastic estimation theory -- Reverse-correlation and spike train decoding -- Signal detection theory -- Relating neuronal responses and psychophysics -- Population codes -- Neuronal networks -- Solutions to selected exercises.

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  ▼a  Computational neuroscience.

• 650

  ▼a  Computational biology.

• 650

  ▼a  Neurosciences.

• 650

  ▼a  Computational Biology
  ▼x  methods

• 650

  ▼a  Mathematical Concepts

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  ▼a  Models, Neurological

• 650

  ▼a  Nerve Net

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  ▼a  Neurons
  ▼x  physiology

• 650

  ▼a  Neurosciences
  ▼x  methods

• 650

  ▼a  Synaptic Transmission

• 700

  ▼a  Cox, Steven J.
  ▼q  (Steven James),
  ▼d  1960-,

• 991

  ▼a  단행본

• 090

  ▼a  612.8
  ▼b  G112m