Feature extraction from spike trains with Bayesian binning: 'Latency is where the signal starts'

Journal of Computational Neuroscience

Volumn 29, Issue 1-2, 2010, Pages 149-169

  Endres, Dominik ^a   Oram, Mike ^a  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

Author keywords

Bayesian methods; Information theory; PSTH; Response latency; SDF; Spike train analysis

Indexed keywords

BAYESIAN NETWORKS; EXTRACTION; INFORMATION THEORY; LEARNING SYSTEMS; NEURONS; OPEN SOURCE SOFTWARE; OPEN SYSTEMS;

BAYESIAN; BAYESIAN METHODS; FEATURES EXTRACTION; FIRING RATES; PERISTIMULU TIME HISTOGRAM; POSTERIOR DISTRIBUTIONS; RESPONSE LATENCY; SPIKE DENSITY FUNCTION; SPIKE TRAIN; SPIKE TRAIN ANALYSIS;

FEATURE EXTRACTION;

ACCURACY; ARTICLE; BAYES THEOREM; COMPUTER PROGRAM; CONTROLLED STUDY; INTERMETHOD COMPARISON; KERNEL METHOD; LATENT PERIOD; MACHINE LEARNING; NERVE CELL; NEUROPHYSIOLOGY; PREDICTION; PRIORITY JOURNAL; SIMULATION; SPIKE; STATISTICAL MODEL;

EID: 77956945292     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10827-009-0157-3     Document Type: Article

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