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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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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 :
Yusoff, N
Grüning, A
Notley, S
Date : 2012
DOI : 10.1007/978-3-642-33269-2_18
Contributors :
Additional Information : The original publication is available at
Depositing User : Symplectic Elements
Date Deposited : 25 Feb 2014 14:43
Last Modified : 31 Oct 2017 14:41

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