Yusoff, Nooraini and Ahmad, Farzana Kabir (2014) Spiking neural network with lateral inhibition for reward-based associative learning. In: Neural Information Processing. Lecture Notes in Computer Science, 8834 . Springer International Publishing, Switzerland, pp. 327-334. ISBN 978-3-319-12636-4

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Abstract

In this paper we propose a lateral inhibitory spiking neural network for reward-based associative learning with correlation in spike patterns for conflicting responses. The network has random and sparse connectivity, and we introduce a lateral inhibition via an anatomical constraint and synapse reinforcement. The spiking dynamic follows the properties of Izhikevich spiking model. The learning involves association of a delayed stimulus pair to a response using reward modulated spike-time dependent plasticity (STDP). The proposed learning scheme has improved our initial work by allowing learning in a more dynamic and competitive environment.

Item Type:	Book Section
Uncontrolled Keywords:	Lateral inhibition. Spiking neural network. Associative Learning. Spike-time dependent plasticity.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Dr. Nooraini Yusoff
Date Deposited:	04 Oct 2016 08:08
Last Modified:	04 Oct 2016 08:08
URI:	https://repo.uum.edu.my/id/eprint/18762

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