An information-geometric framework for statistical inferences in the neural spike train space

Journal of Computational Neuroscience

Volumn 31, Issue 3, 2011, Pages 725-748

  Wu, Wei ^a   Srivastava, Anuj ^a  

^a FLORIDA STATE UNIVERSITY   (United States)

Author keywords

Information geometry; Spike train metrics; Spike train space; Statistical inferences

Indexed keywords

STATISTICAL METHODS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; TIME DOMAIN ANALYSIS;

'CURRENT; COMPUTATIONAL NEUROSCIENCE; GEOMETRIC FRAMEWORK; INFORMATION GEOMETRY; NEURAL SPIKE TRAINS; SPIKE TRAIN; SPIKE TRAIN METRIC; SPIKE TRAIN SPACE; STATISTICAL INFERENCE;

RANDOM PROCESSES;

ACCURACY; ARTICLE; CLASSIFICATION ALGORITHM; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; METRIC SYSTEM; MOTOR CORTEX; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROCESS MODEL; SPIKE WAVE; STATISTICAL ANALYSIS; STOCHASTIC MODEL;

EID: 83055194741     PISSN: 09295313     EISSN: 15736873     Source Type: Journal    
DOI: 10.1007/s10827-011-0336-x     Document Type: Article

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