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Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network

Striatal medium spiny neurons (MSNs) receive lateral inhibitory projections from other MSNs and feedforward inhibitory projections from fast-spiking, parvalbumin-containing striatal interneurons (FSIs). The functional roles of these connections are unknown, and difficult to study in an experimental...

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Autores principales: Moyer, Jason T., Halterman, Benjamin L., Finkel, Leif H., Wolf, John A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4243567/
https://www.ncbi.nlm.nih.gov/pubmed/25505406
http://dx.doi.org/10.3389/fncom.2014.00152
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author Moyer, Jason T.
Halterman, Benjamin L.
Finkel, Leif H.
Wolf, John A.
author_facet Moyer, Jason T.
Halterman, Benjamin L.
Finkel, Leif H.
Wolf, John A.
author_sort Moyer, Jason T.
collection PubMed
description Striatal medium spiny neurons (MSNs) receive lateral inhibitory projections from other MSNs and feedforward inhibitory projections from fast-spiking, parvalbumin-containing striatal interneurons (FSIs). The functional roles of these connections are unknown, and difficult to study in an experimental preparation. We therefore investigated the functionality of both lateral (MSN-MSN) and feedforward (FSI-MSN) inhibition using a large-scale computational model of the striatal network. The model consists of 2744 MSNs comprised of 189 compartments each and 121 FSIs comprised of 148 compartments each, with dendrites explicitly represented and almost all known ionic currents included and strictly constrained by biological data as appropriate. Our analysis of the model indicates that both lateral inhibition and feedforward inhibition function at the population level to limit non-ensemble MSN spiking while preserving ensemble MSN spiking. Specifically, lateral inhibition enables large ensembles of MSNs firing synchronously to strongly suppress non-ensemble MSNs over a short time-scale (10–30 ms). Feedforward inhibition enables FSIs to strongly inhibit weakly activated, non-ensemble MSNs while moderately inhibiting activated ensemble MSNs. Importantly, FSIs appear to more effectively inhibit MSNs when FSIs fire asynchronously. Both types of inhibition would increase the signal-to-noise ratio of responding MSN ensembles and contribute to the formation and dissolution of MSN ensembles in the striatal network.
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spelling pubmed-42435672014-12-10 Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network Moyer, Jason T. Halterman, Benjamin L. Finkel, Leif H. Wolf, John A. Front Comput Neurosci Neuroscience Striatal medium spiny neurons (MSNs) receive lateral inhibitory projections from other MSNs and feedforward inhibitory projections from fast-spiking, parvalbumin-containing striatal interneurons (FSIs). The functional roles of these connections are unknown, and difficult to study in an experimental preparation. We therefore investigated the functionality of both lateral (MSN-MSN) and feedforward (FSI-MSN) inhibition using a large-scale computational model of the striatal network. The model consists of 2744 MSNs comprised of 189 compartments each and 121 FSIs comprised of 148 compartments each, with dendrites explicitly represented and almost all known ionic currents included and strictly constrained by biological data as appropriate. Our analysis of the model indicates that both lateral inhibition and feedforward inhibition function at the population level to limit non-ensemble MSN spiking while preserving ensemble MSN spiking. Specifically, lateral inhibition enables large ensembles of MSNs firing synchronously to strongly suppress non-ensemble MSNs over a short time-scale (10–30 ms). Feedforward inhibition enables FSIs to strongly inhibit weakly activated, non-ensemble MSNs while moderately inhibiting activated ensemble MSNs. Importantly, FSIs appear to more effectively inhibit MSNs when FSIs fire asynchronously. Both types of inhibition would increase the signal-to-noise ratio of responding MSN ensembles and contribute to the formation and dissolution of MSN ensembles in the striatal network. Frontiers Media S.A. 2014-11-25 /pmc/articles/PMC4243567/ /pubmed/25505406 http://dx.doi.org/10.3389/fncom.2014.00152 Text en Copyright © 2014 Moyer, Halterman, Finkel and Wolf. 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) or licensor 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
Moyer, Jason T.
Halterman, Benjamin L.
Finkel, Leif H.
Wolf, John A.
Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
title Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
title_full Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
title_fullStr Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
title_full_unstemmed Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
title_short Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
title_sort lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4243567/
https://www.ncbi.nlm.nih.gov/pubmed/25505406
http://dx.doi.org/10.3389/fncom.2014.00152
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