Learning Anticipation through Priming in Spatio-temporal Neural Networks [chapter]

Nooraini Yusoff, André Grüning
2012 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 facilitate
more » ... e response to a later stimulus. The network can be trained to associate a stimulus pair (with an inter-stimulus interval) to a response, as well as to recognise the temporal sequence of the stimulus presentation.
doi:10.1007/978-3-642-34475-6_21 fatcat:pzqrb7vtcze43derwmx3u6bh2a