Combining spatial and parametric working memory in a dynamic neural field model

We present a novel dynamic neural field model consisting of two coupled fields of Amari-type which supports the existence of localized activity patterns or “bumps” with a continuum of amplitudes. Bump solutions have been used in the past to model spatial working memory. We apply the model to explain...

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Main Authors: Wojtak, Weronika, Coombes, Stephen, Bicho, Estela, Erlhagen, Wolfram
Format: Article
Published: Springer Verlag 2016
Online Access:https://eprints.nottingham.ac.uk/40913/
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author Wojtak, Weronika
Coombes, Stephen
Bicho, Estela
Erlhagen, Wolfram
author_facet Wojtak, Weronika
Coombes, Stephen
Bicho, Estela
Erlhagen, Wolfram
author_sort Wojtak, Weronika
building Nottingham Research Data Repository
collection Online Access
description We present a novel dynamic neural field model consisting of two coupled fields of Amari-type which supports the existence of localized activity patterns or “bumps” with a continuum of amplitudes. Bump solutions have been used in the past to model spatial working memory. We apply the model to explain input-specific persistent activity that increases monotonically with the time integral of the input (parametric working memory). In numerical simulations of a multi-item memory task, we show that the model robustly memorizes the strength and/or duration of inputs. Moreover, and important for adaptive behavior in dynamic environments, the memory strength can be changed at any time by new behaviorally relevant information. A direct comparison of model behaviors shows that the 2-field model does not suffer the problems of the classical Amari model when the inputs are presented sequentially as opposed to simultaneously.
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spelling nottingham-409132020-05-04T18:07:04Z https://eprints.nottingham.ac.uk/40913/ Combining spatial and parametric working memory in a dynamic neural field model Wojtak, Weronika Coombes, Stephen Bicho, Estela Erlhagen, Wolfram We present a novel dynamic neural field model consisting of two coupled fields of Amari-type which supports the existence of localized activity patterns or “bumps” with a continuum of amplitudes. Bump solutions have been used in the past to model spatial working memory. We apply the model to explain input-specific persistent activity that increases monotonically with the time integral of the input (parametric working memory). In numerical simulations of a multi-item memory task, we show that the model robustly memorizes the strength and/or duration of inputs. Moreover, and important for adaptive behavior in dynamic environments, the memory strength can be changed at any time by new behaviorally relevant information. A direct comparison of model behaviors shows that the 2-field model does not suffer the problems of the classical Amari model when the inputs are presented sequentially as opposed to simultaneously. Springer Verlag 2016-08-13 Article PeerReviewed Wojtak, Weronika, Coombes, Stephen, Bicho, Estela and Erlhagen, Wolfram (2016) Combining spatial and parametric working memory in a dynamic neural field model. Lecture Notes in Computer Science, 9886 . pp. 411-418. ISSN 0302-9743 http://link.springer.com/chapter/10.1007/978-3-319-44778-0_48 doi:10.1007/978-3-319-44778-0_48 doi:10.1007/978-3-319-44778-0_48
spellingShingle Wojtak, Weronika
Coombes, Stephen
Bicho, Estela
Erlhagen, Wolfram
Combining spatial and parametric working memory in a dynamic neural field model
title Combining spatial and parametric working memory in a dynamic neural field model
title_full Combining spatial and parametric working memory in a dynamic neural field model
title_fullStr Combining spatial and parametric working memory in a dynamic neural field model
title_full_unstemmed Combining spatial and parametric working memory in a dynamic neural field model
title_short Combining spatial and parametric working memory in a dynamic neural field model
title_sort combining spatial and parametric working memory in a dynamic neural field model
url https://eprints.nottingham.ac.uk/40913/
https://eprints.nottingham.ac.uk/40913/
https://eprints.nottingham.ac.uk/40913/