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Adaptive Surround Modulation of MT Neurons: A Computational Model

The classical receptive field (CRF) of a spiking visual neuron is defined as the region in the visual field that can generate spikes when stimulated by a visual stimulus. Many visual neurons also have an extra-classical receptive field (ECRF) that surrounds the CRF. The presence of a stimulus in the...

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Autores principales: Zarei Eskikand, Parvin, Kameneva, Tatiana, Burkitt, Anthony N., Grayden, David B., Ibbotson, Michael R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649322/
https://www.ncbi.nlm.nih.gov/pubmed/33192335
http://dx.doi.org/10.3389/fncir.2020.529345
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author Zarei Eskikand, Parvin
Kameneva, Tatiana
Burkitt, Anthony N.
Grayden, David B.
Ibbotson, Michael R.
author_facet Zarei Eskikand, Parvin
Kameneva, Tatiana
Burkitt, Anthony N.
Grayden, David B.
Ibbotson, Michael R.
author_sort Zarei Eskikand, Parvin
collection PubMed
description The classical receptive field (CRF) of a spiking visual neuron is defined as the region in the visual field that can generate spikes when stimulated by a visual stimulus. Many visual neurons also have an extra-classical receptive field (ECRF) that surrounds the CRF. The presence of a stimulus in the ECRF does not generate spikes but rather modulates the response to a stimulus in the neuron's CRF. Neurons in the primate Middle Temporal (MT) area, which is a motion specialist region, can have directionally antagonistic or facilitatory surrounds. The surround's effect switches between directionally antagonistic or facilitatory based on the characteristics of the stimulus, with antagonistic effects when there are directional discontinuities but facilitatory effects when there is directional coherence. Here, we present a computational model of neurons in area MT that replicates this observation and uses computational building blocks that correlate with observed cell types in the visual pathways to explain the mechanism of this modulatory effect. The model shows that the categorization of MT neurons based on the effect of their surround depends on the input stimulus rather than being a property of the neurons. Also, in agreement with neurophysiological findings, the ECRFs of the modeled MT neurons alter their center-surround interactions depending on image contrast.
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spelling pubmed-76493222020-11-13 Adaptive Surround Modulation of MT Neurons: A Computational Model Zarei Eskikand, Parvin Kameneva, Tatiana Burkitt, Anthony N. Grayden, David B. Ibbotson, Michael R. Front Neural Circuits Neuroscience The classical receptive field (CRF) of a spiking visual neuron is defined as the region in the visual field that can generate spikes when stimulated by a visual stimulus. Many visual neurons also have an extra-classical receptive field (ECRF) that surrounds the CRF. The presence of a stimulus in the ECRF does not generate spikes but rather modulates the response to a stimulus in the neuron's CRF. Neurons in the primate Middle Temporal (MT) area, which is a motion specialist region, can have directionally antagonistic or facilitatory surrounds. The surround's effect switches between directionally antagonistic or facilitatory based on the characteristics of the stimulus, with antagonistic effects when there are directional discontinuities but facilitatory effects when there is directional coherence. Here, we present a computational model of neurons in area MT that replicates this observation and uses computational building blocks that correlate with observed cell types in the visual pathways to explain the mechanism of this modulatory effect. The model shows that the categorization of MT neurons based on the effect of their surround depends on the input stimulus rather than being a property of the neurons. Also, in agreement with neurophysiological findings, the ECRFs of the modeled MT neurons alter their center-surround interactions depending on image contrast. Frontiers Media S.A. 2020-10-26 /pmc/articles/PMC7649322/ /pubmed/33192335 http://dx.doi.org/10.3389/fncir.2020.529345 Text en Copyright © 2020 Zarei Eskikand, Kameneva, Burkitt, Grayden and Ibbotson. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Zarei Eskikand, Parvin
Kameneva, Tatiana
Burkitt, Anthony N.
Grayden, David B.
Ibbotson, Michael R.
Adaptive Surround Modulation of MT Neurons: A Computational Model
title Adaptive Surround Modulation of MT Neurons: A Computational Model
title_full Adaptive Surround Modulation of MT Neurons: A Computational Model
title_fullStr Adaptive Surround Modulation of MT Neurons: A Computational Model
title_full_unstemmed Adaptive Surround Modulation of MT Neurons: A Computational Model
title_short Adaptive Surround Modulation of MT Neurons: A Computational Model
title_sort adaptive surround modulation of mt neurons: a computational model
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649322/
https://www.ncbi.nlm.nih.gov/pubmed/33192335
http://dx.doi.org/10.3389/fncir.2020.529345
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