Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity

Journal of Computational Neuroscience

Volumn 39, Issue 3, 2015, Pages 311-327

  Ly, Cheng ^a  

^a VIRGINIA COMMONWEALTH UNIVERSITY   (United States)

Author keywords

Dimension reduction; Intrinsic heterogeneity; Leaky integrate and fire; Network heterogeneity; Recurrent E I network

Indexed keywords

CELLULAR NEURAL NETWORKS; INTELLIGENT SYSTEMS; MONTE CARLO METHODS; NEURAL NETWORK MODELS; PROBABILITY DENSITY FUNCTION; RECURRENT NEURAL NETWORKS;

ANALYTIC DESCRIPTIONS; DIMENSION REDUCTION; DIMENSION REDUCTION METHOD; FIRING RATES; INTEGRATE AND FIRES; INTRINSIC HETEROGENEITY; LEAKY INTEGRATE-AND-FIRE; NETWORK HETEROGENEITY; NEURAL-NETWORKS; RECURRENT E/I NETWORK;

DYNAMICS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CALCULATION; MATHEMATICAL ANALYSIS; MONTE CARLO METHOD; NERVE CELL; PRIORITY JOURNAL; PROBABILITY; SIMULATION; VALIDITY; ACTION POTENTIAL; ANIMAL; BIOLOGICAL MODEL; BRAIN CORTEX; COMPUTER SIMULATION; CYTOLOGY; HUMAN; MARKOV CHAIN; MOUSE; NERVE CELL NETWORK; PHYSIOLOGY;

ACTION POTENTIALS; ANIMALS; CEREBRAL CORTEX; COMPUTER SIMULATION; HUMANS; MICE; MODELS, NEUROLOGICAL; MONTE CARLO METHOD; NERVE NET; NEURAL NETWORKS (COMPUTER); STOCHASTIC PROCESSES;

EID: 84947491872     PISSN: 09295313     EISSN: 15736873     Source Type: Journal    
DOI: 10.1007/s10827-015-0578-0     Document Type: Article

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