Pseudo-Lyapunov exponents and predictability of Hodgkin-Huxley neuronal network dynamics

Journal of Computational Neuroscience

Volumn 28, Issue 2, 2010, Pages 247-266

  Sun, Yi ^a   Zhou, Douglas ^a   Rangan, Aaditya V ^a   Cai, David ^a,b  

^a NEW YORK UNIVERSITY   (United States)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Chaos; Hodgkin Huxley neuron; Lyapunov exponents; Neuronal network; Numerical analysis

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; DIFFERENTIAL EQUATIONS; LYAPUNOV METHODS; NEURONS; SPECTRUM ANALYSIS;

CHAOTICS; DYNAMICAL REGIME; HODGKIN-HUXLEY NEURON; LYAPUNOV EXPONENT; NETWORK DYNAMICS; NEURONAL NETWORKS; NUMERICAL CONVERGENCE; NUMERICAL RESULTS; PSEUDO-LYAPUNOV-EXPONENT; STRONG-COUPLING;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; HODGKIN HUXLEY EQUATION; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; POISSON DISTRIBUTION; PREDICTION; PRIORITY JOURNAL; PSEUDO LYAPUNOV EXPONENT; STATISTICAL ANALYSIS; SYNAPTIC TRANSMISSION;

EID: 77953322930     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10827-009-0202-2     Document Type: Article

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