LEARNING STIMULUS-STIMULUS ASSOCIATION IN SPATIO-TEMPORAL NEURAL NETWORKS
DOI:
https://doi.org/10.11113/jt.v77.6126Keywords:
Associative learning, stimulus-stimulus association, spatio-temporal neural networks, spike-timing dependent plasticityAbstract
We propose a stimulus-stimulus association learning by coupling firing rate and precise spike timing encoding for spatio-temporal neural networks. We simulate a generic recurrent network with random and sparse connectivity consisting of Izhikevich spiking neurons. The magnitude of weight adjustment in learning is dependent on pre- and postsynaptic spikes based on their spikes count and time correlation. As a result of learning, synchronisation of activity among inter- and intra-subpopulation neurons demonstrates association between two stimuli. The associations show in spill-over of activity between the two stimuli involved.Â
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