Spike-time reliability of layered neural oscillator networks

Journal of Computational Neuroscience

Volumn 27, Issue 1, 2009, Pages 135-160

  Lin, Kevin K ^a   Shea Brown, Eric ^b   Young, Lai Sang ^c  

^a University of Arizona   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

^c NEW YORK UNIVERSITY   (United States)

Author keywords

Chaos; Neural oscillator; Random dynamical systems; Spike time reliability; Spiking neural network; Stochastic dynamics; Theta neuron

Indexed keywords

DYNAMICAL SYSTEMS; NETWORK LAYERS; NEURAL NETWORKS; RELIABILITY; STOCHASTIC SYSTEMS;

INITIAL CONDITIONS; LAYERED NETWORK; NEURAL OSCILLATOR; NEURAL OSCILLATOR NETWORK; NEURAL-NETWORKS; RANDOM DYNAMICAL SYSTEM; SPIKE-TIME RELIABILITY; SPIKING NEURAL NETWORK; STOCHASTIC DYNAMICS; THETA NEURON;

NEURONS;

ARTICLE; CELL POPULATION; FEEDBACK SYSTEM; NERVE CELL NETWORK; NOISE STANDARD; OSCILLATORY POTENTIAL; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; RELIABILITY; SPIKE; STOCHASTIC MODEL; SYNAPTIC TRANSMISSION; THETA RHYTHM;

ACTION POTENTIALS; ANIMALS; CELL COUNT; FEEDBACK, PSYCHOLOGICAL; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); NEURONS; PERIODICITY; STOCHASTIC PROCESSES; SYNAPTIC TRANSMISSION; TIME FACTORS;

EID: 68349141313     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10827-008-0133-3     Document Type: Article

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