Learning anticipation through priming in spatio-temporal neural networks
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 depende...
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my.uum.repo.124882014-10-26T02:29:22Z http://repo.uum.edu.my/12488/ Learning anticipation through priming in spatio-temporal neural networks Yusoff, Nooraini Grüning, André QA76 Computer software 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 the 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. Springer Tingwen, Huang Zhigang, Zeng Chuangdong, Li Chi, Sing Leung 2012 Book Section PeerReviewed Yusoff, Nooraini and Grüning, André (2012) Learning anticipation through priming in spatio-temporal neural networks. In: Neural Information Processing. Lecture Notes in Computer Science, 7663 (7663). Springer, pp. 168-175. ISBN 978-3-642-34474-9 http://dx.doi.org/10.1007/978-3-642-34475-6_21 doi:10.1007/978-3-642-34475-6_21 |
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QA76 Computer software Yusoff, Nooraini Grüning, André Learning anticipation through priming in spatio-temporal neural networks |
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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 the 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. |
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Tingwen, Huang |
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Tingwen, Huang Yusoff, Nooraini Grüning, André |
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Book Section |
author |
Yusoff, Nooraini Grüning, André |
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Yusoff, Nooraini |
title |
Learning anticipation through priming in spatio-temporal neural networks |
title_short |
Learning anticipation through priming in spatio-temporal neural networks |
title_full |
Learning anticipation through priming in spatio-temporal neural networks |
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Learning anticipation through priming in spatio-temporal neural networks |
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Learning anticipation through priming in spatio-temporal neural networks |
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learning anticipation through priming in spatio-temporal neural networks |
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Springer |
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2012 |
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http://repo.uum.edu.my/12488/ http://dx.doi.org/10.1007/978-3-642-34475-6_21 |
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