How noisy adaptation of neurons shapes interspike interval histograms and correlations

PLoS Computational Biology

Volumn 6, Issue 12, 2010, Pages

  Schwalger, Tilo ^a   Fisch, Karin ^b   Benda, Jan ^b   Lindner, Benjamin ^a  

^a MAX PLANCK INSTITUT FÜR PHYSIK KOMPLEXER SYSTEME   (Germany)

^b UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROPHYSIOLOGY; NUMERICAL MODELS; SPURIOUS SIGNAL NOISE; STOCHASTIC SYSTEMS;

'CURRENT; ACTION-POTENTIALS; CHANNEL NOISE; DETERMINISTICS; INTER SPIKE INTERVALS; INTRINSIC NOISE; NOISE SOURCE; SERIAL CORRELATION; SHAPE RESPONSE; STOCHASTICS;

NEURONS;

SODIUM CHANNEL;

ARTICLE; CELL ACTIVITY; DIFFUSION COEFFICIENT; HISTOGRAM; HODGKIN HUXLEY EQUATION; MOLECULAR EVOLUTION; NERVE CELL MEMBRANE POTENTIAL; NOISE; NOISE REDUCTION; NORMAL DISTRIBUTION; PROCESS MODEL; SIGNAL TRANSDUCTION; SODIUM CURRENT; SPIKE WAVE; STATISTICAL ANALYSIS; STOCHASTIC MODEL; WHITE NOISE; ACTION POTENTIAL; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; METHODOLOGY; NERVE CELL; PHYSIOLOGY; STATISTICS;

ACTION POTENTIALS; ALGORITHMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; MODELS, NEUROLOGICAL; NEURONS; NORMAL DISTRIBUTION; STOCHASTIC PROCESSES;

EID: 78651247361     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1001026     Document Type: Article

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