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Lecture Notes in Computer Science
In this paper, we propose a reward-based learning model inspired by the findings from a behavioural study and biologically realistic properties of spatio-temporal neural networks. The model simulates the cognitive priming effect in stimulus-stimulus-response association. Synaptic plasticity is dependent on a global reward signal that enhances the synaptic changes derived from spike-timing dependent plasticity (STDP) process. We show that by priming a network with a cue stimulus can facilitatedoi:10.1007/978-3-642-34475-6_21 fatcat:pzqrb7vtcze43derwmx3u6bh2a