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Mathematics for neuroscientists

By: Gabbiani, Fabrizio.
Contributor(s): Cox, Steven J 1960-.
Material type: materialTypeLabelBookPublisher: Boston : Academic Press, ©2010Description: x, 486 p. : ill. (some col.) ; 28 cm.ISBN: 9780123748829.Subject(s): Computational Biology -- methods | Models, Neurological | Nerve Net | Neurons -- physiology | Neurosciences -- methods | Synaptic Transmission
Contents:
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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Books Books IIITD
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Engineering and Allied Operation REF 612.8 GAB-M (Browse shelf) Available 004349
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Includes bibliographical references (p. 473-482) and index.

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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