Networks that learn the precise timing of event sequences

Journal of Computational Neuroscience

Volumn 39, Issue 3, 2015, Pages 235-254

  Veliz Cuba, Alan ^a   Shouval, Harel Z ^b   Josić, Krešimir ^a   Kilpatrick, Zachary P ^a  

^a University of Houston   (United States)

^b UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

Author keywords

Long term plasticity; Serial recall; Short term facilitation

Indexed keywords

REAL TIME SYSTEMS; TIMING CIRCUITS;

EVENT SEQUENCE; FIRING PATTERNS; LEARN+; LONG TERM PLASTICITY; NETWORK MODELS; NEURONAL CIRCUITS; SEQUENCE LEARNING; SERIAL RECALL; SHORT TERM; SHORT TERM FACILITATION;

NEURONS;

ARTICLE; FACILITATION; FIRING RATE; HUMAN; LEARNING; LONG TERM DEPRESSION; LONG TERM POTENTIATION; NERVE CELL NETWORK; NERVE CELL PLASTICITY; PRIORITY JOURNAL; SENSORY STIMULATION; SPATIOTEMPORAL ANALYSIS; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; COMPUTER SIMULATION; MACHINE LEARNING; PHYSIOLOGY; PYRAMIDAL NERVE CELL; SYNAPSE; TIME; TIME PERCEPTION;

COMPUTER SIMULATION; HUMANS; LEARNING; MACHINE LEARNING; MODELS, NEUROLOGICAL; NERVE NET; NEURAL NETWORKS (COMPUTER); NEURONAL PLASTICITY; PYRAMIDAL CELLS; SYNAPSES; TIME; TIME PERCEPTION;

EID: 84947496262     PISSN: 09295313     EISSN: 15736873     Source Type: Journal    
DOI: 10.1007/s10827-015-0574-4     Document Type: Article

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