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Spatio-temporal event association using reward-modulated spike-time-dependent plasticity

For goal-directed learning in spiking neural networks, target spike templates are usually required.Optimal performance is achieved by minimising the error between the desired and output spike timings.However, in some dynamic environments, a set of learning targets with precise encoding is not always...

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Main Authors: Yusoff, Nooraini, Ibrahim, Mohammed Fadhil
Format: Article
Published: Elsevier B.V. 2018
Subjects:
LB Theory and practice of education
Online Access:http://repo.uum.edu.my/24363/
http://doi.org/10.1016/j.ins.2018.03.043
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spelling my.uum.repo.243632018-07-04T01:51:42Z http://repo.uum.edu.my/24363/ Spatio-temporal event association using reward-modulated spike-time-dependent plasticity Yusoff, Nooraini Ibrahim, Mohammed Fadhil LB Theory and practice of education For goal-directed learning in spiking neural networks, target spike templates are usually required.Optimal performance is achieved by minimising the error between the desired and output spike timings.However, in some dynamic environments, a set of learning targets with precise encoding is not always available.For this study, we associate a pair of spatio-temporal events with a target response using a reinforcement learning approach.The learning is implemented in a recurrent spiking neural network using reward-modulated spike-time-dependent plasticity.The learning protocol is simple and inspired by a behavioural experiment from a neuropsychology study.For a goal-directed application, learning does not require a target spike template.In this study, convergence is measured by synchronicity of activities in associated neuronal groups.As a result of learning, a network is able to associate a pair of events with a temporal delay in a dynamic setting. The results demonstrate that the algorithm can also learn temporal sequence detection.Learning has also been tested in face-voice association using real biometric data.The loose dependency between the model's anatomical properties and functionalities could offer a wide range of applications, especially in complex learning environments. Elsevier B.V. 2018 Article PeerReviewed Yusoff, Nooraini and Ibrahim, Mohammed Fadhil (2018) Spatio-temporal event association using reward-modulated spike-time-dependent plasticity. Information Sciences, 451-45. pp. 143-160. ISSN 00200255 http://doi.org/10.1016/j.ins.2018.03.043 doi:10.1016/j.ins.2018.03.043
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
topic LB Theory and practice of education
spellingShingle LB Theory and practice of education
Yusoff, Nooraini
Ibrahim, Mohammed Fadhil
Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
description For goal-directed learning in spiking neural networks, target spike templates are usually required.Optimal performance is achieved by minimising the error between the desired and output spike timings.However, in some dynamic environments, a set of learning targets with precise encoding is not always available.For this study, we associate a pair of spatio-temporal events with a target response using a reinforcement learning approach.The learning is implemented in a recurrent spiking neural network using reward-modulated spike-time-dependent plasticity.The learning protocol is simple and inspired by a behavioural experiment from a neuropsychology study.For a goal-directed application, learning does not require a target spike template.In this study, convergence is measured by synchronicity of activities in associated neuronal groups.As a result of learning, a network is able to associate a pair of events with a temporal delay in a dynamic setting. The results demonstrate that the algorithm can also learn temporal sequence detection.Learning has also been tested in face-voice association using real biometric data.The loose dependency between the model's anatomical properties and functionalities could offer a wide range of applications, especially in complex learning environments.
format Article
author Yusoff, Nooraini
Ibrahim, Mohammed Fadhil
author_facet Yusoff, Nooraini
Ibrahim, Mohammed Fadhil
author_sort Yusoff, Nooraini
title Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
title_short Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
title_full Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
title_fullStr Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
title_full_unstemmed Spatio-temporal event association using reward-modulated spike-time-dependent plasticity
title_sort spatio-temporal event association using reward-modulated spike-time-dependent plasticity
publisher Elsevier B.V.
publishDate 2018
url http://repo.uum.edu.my/24363/
http://doi.org/10.1016/j.ins.2018.03.043
_version_ 1644284033125842944
score 13.211869

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