Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

Frontiers in Computational Neuroscience

Volumn , Issue OCT, 2013, Pages

  Torre, Emiliano ^a   Picado Muiño, David ^b   Denker, Michael ^a   Borgelt, Christian ^b   Grün, Sonja ^a,c  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

^b EUROPEAN CENTRE FOR SOFT COMPUTING   (Spain)

^c RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

Data mining; Higher order correlations; Multiple testing; Neuronal cell assemblies; Spike patterns; Spike synchrony

Indexed keywords

HIGHER ORDER CORRELATION; MULTIPLE TESTING; NEURONAL CELL; SPIKE PATTERNS; SPIKE SYNCHRONY;

DATA MINING; NEURONS; STOCHASTIC MODELS;

STATISTICAL TESTS;

ARTICLE; CORRELATION ANALYSIS; DATA MINING; FREQUENT ITEM SET MINING; MONTE CARLO METHOD; NERVE CELL; NOMENCLATURE; PATTERN SET REDUCTION; PATTERN SPECTRUM FILTERING; POISSON DISTRIBUTION; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; STOCHASTIC MODEL; SYNCHRONOUS SPIKE PATTERN;

EID: 84888096988     PISSN: 16625188     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncom.2013.00132     Document Type: Article

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