Representation of input structure in synaptic weights by spike-timing-dependent plasticity.
Spike-timing-dependent plasticity (STDP) has been shown to generate a synaptic weight structure that is determined by the timing of the pre- and postsynaptic spikes at the synapse. In this paper it is shown under what conditions a neuron stimulated by several pools of delta-correlated inputs encodes this input structure in its resulting weight structure. The analysis is carried out using Poisson neurons with weight-dependent STDP. The learning dynamics induced by STDP leads to both stabilization of the input weights and competition between the weights for a broad range of learning parameters. The results demonstrate how weight-dependent STDP can generate multimodal stable asymptotic distributions of the synaptic weights.
Gilson
Matthieu
M
Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria, Australia. gilsonm@unimelb.edu.au
Burkitt
Anthony N
AN
Grayden
David B
DB
Thomas
Doreen A
DA
van Hemmen
J Leo
JL
D000200:Action Potentials / Q000502:physiology*; D000222:Adaptation, Physiological / Q000502:physiology; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*