Comparison of information and variance maximization strategies for characterizing neural feature selectivity

Statistics in Medicine

Volumn 26, Issue 21, 2007, Pages 4009-4031

  Sharpee, Tatyana O ^a,b  

^a SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

^b NONE   (United States)

Author keywords

Information theory; Linear nonlinear model; Natural stimuli; R nyi divergences; Receptive fields

Indexed keywords

ANALYSIS OF VARIANCE; ANALYTICAL ERROR; BIOSTATISTICS; BRAIN FUNCTION; COMPARATIVE STUDY; CONFERENCE PAPER; INFORMATION PROCESSING; MATHEMATICAL ANALYSIS; NERVE POTENTIAL; NOISE; NONLINEAR SYSTEM; PREDICTION; PROBABILITY; QUANTITATIVE ANALYSIS; SIGNAL NOISE RATIO; SPIKE; STATISTICAL ANALYSIS; STATISTICAL MODEL; STIMULUS RESPONSE;

ANALYSIS OF VARIANCE; BIOMETRY; ELECTROENCEPHALOGRAPHY; HUMANS; INFORMATION THEORY; MODELS, STATISTICAL; NEURONS; UNITED STATES;

EID: 34548382490     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.2931     Document Type: Conference Paper

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