Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity-strengthening correlated input pathways

Biological Cybernetics

Volumn 101, Issue 2, 2009, Pages 81-102

  Gilson, Matthieu ^a   Burkitt, Anthony N ^a,b,c   Grayden, David B ^a,b,c   Thomas, Doreen A ^a,c   Van Hemmen, J Leo ^d  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b BIONIC EAR INSTITUTE   (Australia)

^c CSIRO   (Australia)

^d TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Learning; Recurrent neuronal network; Spike time correlation; STDP

Indexed keywords

ASYMPTOTIC STATE; FEED-FORWARD NETWORK; FIRING RATES; INPUT NEURONS; LEARNING; NETWORK DYNAMICS; NETWORK STRUCTURES; NEURON FIRING; NEURON MODEL; NEURONAL ACTIVITIES; NEURONAL NETWORKS; PLASTIC CONNECTIONS; POST-SYNAPTIC POTENTIALS; RECURRENT NEURONAL NETWORK; SINGLE NEURON; SPIKE TRAIN; SPIKE-TIME CORRELATION; SPIKE-TIMING-DEPENDENT PLASTICITY; STDP; SYNAPTIC DELAYS; SYNAPTIC DYNAMICS; SYNAPTIC WEIGHT; THEORETICAL FRAMEWORK; TIME CORRELATIONS; TIME COURSE;

LAKES; LOCOMOTIVES; NEURAL NETWORKS; NEURONS; PLASTICITY; POISSON DISTRIBUTION; POISSON EQUATION; RAILROAD CARS; SIGNAL ENCODING; TIME MEASUREMENT;

ASYMPTOTIC ANALYSIS;

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; BRAIN; HUMAN; NERVE CELL; NERVE CELL NETWORK; NERVE CELL PLASTICITY; PHYSIOLOGY; SYNAPTIC POTENTIAL; SYNAPTIC TRANSMISSION;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; BRAIN; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURONAL PLASTICITY; NEURONS; SYNAPTIC POTENTIALS; SYNAPTIC TRANSMISSION;

EID: 68949211777     PISSN: 03401200     EISSN: 14320770     Source Type: Journal    
DOI: 10.1007/s00422-009-0319-4     Document Type: Article

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