Pair-associate Learning with Modulated Spike-Time Dependent Plasticity

Yusoff, N, Grüning, A and Notley, S (2012) Pair-associate Learning with Modulated Spike-Time Dependent Plasticity In: 22nd International Conference on Artificial Neural Networks, 2012-09-11 - 2012-09-14, Lausanne, Switzerland.

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Abstract

We propose an associative learning model using reward mod- ulated spike-time dependent plasticity in reinforcement learning paradigm. The task of learning is to associate a stimulus pair, known as the predictor− choice pair, to a target response. In our model, a generic architecture of neural network has been used, with minimal assumption about the network dynamics. We demonstrate that stimulus-stimulus-response as- sociation can be implemented in a stochastic way within a noisy setting. The network has rich dynamics resulting from its recurrent connectiv- ity and background activity. The algorithm can learn temporal sequence detection and solve temporal XOR problem.

Item Type:	Conference or Workshop Item (Conference Paper)
Divisions :	Faculty of Engineering and Physical Sciences > Computing Science
Authors :	Name Email ORCID Yusoff, N Grüning, A Notley, S
Date :	2012
DOI :	10.1007/978-3-642-33269-2_18
Contributors :	Contribution Name Email ORCID http://www.loc.gov/loc.terms/relators/PBL Springer,
Additional Information :	The original publication is available at http://www.springerlink.com
Depositing User :	Symplectic Elements
Date Deposited :	25 Feb 2014 14:43
Last Modified :	31 Oct 2017 14:41
URI:	http://epubs.surrey.ac.uk/id/eprint/713372

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