Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire model

Journal of Computational Neuroscience

Volumn 24, Issue 1, 2008, Pages 69-79

  Paninski, Liam ^a   Haith, Adrian ^b   Szirtes, Gabor ^a  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Large deviations approximation; Markov process; Volterra integral equation

Indexed keywords

INTEGRAL EQUATIONS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

FIRST-PASSAGE-TIME DENSITY; FREE PARAMETERS; GRADIENTS COMPUTATION; INTEGRAL EQUATION METHODS; INTEGRATE-AND-FIRE MODEL; LARGE DEVIATION APPROXIMATION; LARGE DEVIATIONS; SPIKE TRAIN; STOCHASTICS; VOLTERRA INTEGRAL EQUATIONS;

MARKOV PROCESSES;

ARTICLE; COMPUTER LANGUAGE; CONDUCTANCE; HIDDEN MARKOV MODEL; KERNEL METHOD; NERVE CONDUCTION; NEUROSCIENCE; PRIORITY JOURNAL; PROBABILITY; SPIKE WAVE;

EID: 38549175663     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10827-007-0042-x     Document Type: Article

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