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Inhibitory Plasticity: From Molecules to Computation and Beyond

Synaptic plasticity is the cellular and molecular counterpart of learning and memory and, since its first discovery, the analysis of the mechanisms underlying long-term changes of synaptic strength has been almost exclusively focused on excitatory connections. Conversely, inhibition was considered a...

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Detalles Bibliográficos
Autores principales: Gandolfi, Daniela, Bigiani, Albertino, Porro, Carlo Adolfo, Mapelli, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7084224/
https://www.ncbi.nlm.nih.gov/pubmed/32155701
http://dx.doi.org/10.3390/ijms21051805
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author Gandolfi, Daniela
Bigiani, Albertino
Porro, Carlo Adolfo
Mapelli, Jonathan
author_facet Gandolfi, Daniela
Bigiani, Albertino
Porro, Carlo Adolfo
Mapelli, Jonathan
author_sort Gandolfi, Daniela
collection PubMed
description Synaptic plasticity is the cellular and molecular counterpart of learning and memory and, since its first discovery, the analysis of the mechanisms underlying long-term changes of synaptic strength has been almost exclusively focused on excitatory connections. Conversely, inhibition was considered as a fixed controller of circuit excitability. Only recently, inhibitory networks were shown to be finely regulated by a wide number of mechanisms residing in their synaptic connections. Here, we review recent findings on the forms of inhibitory plasticity (IP) that have been discovered and characterized in different brain areas. In particular, we focus our attention on the molecular pathways involved in the induction and expression mechanisms leading to changes in synaptic efficacy, and we discuss, from the computational perspective, how IP can contribute to the emergence of functional properties of brain circuits.
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spelling pubmed-70842242020-03-24 Inhibitory Plasticity: From Molecules to Computation and Beyond Gandolfi, Daniela Bigiani, Albertino Porro, Carlo Adolfo Mapelli, Jonathan Int J Mol Sci Review Synaptic plasticity is the cellular and molecular counterpart of learning and memory and, since its first discovery, the analysis of the mechanisms underlying long-term changes of synaptic strength has been almost exclusively focused on excitatory connections. Conversely, inhibition was considered as a fixed controller of circuit excitability. Only recently, inhibitory networks were shown to be finely regulated by a wide number of mechanisms residing in their synaptic connections. Here, we review recent findings on the forms of inhibitory plasticity (IP) that have been discovered and characterized in different brain areas. In particular, we focus our attention on the molecular pathways involved in the induction and expression mechanisms leading to changes in synaptic efficacy, and we discuss, from the computational perspective, how IP can contribute to the emergence of functional properties of brain circuits. MDPI 2020-03-06 /pmc/articles/PMC7084224/ /pubmed/32155701 http://dx.doi.org/10.3390/ijms21051805 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Gandolfi, Daniela
Bigiani, Albertino
Porro, Carlo Adolfo
Mapelli, Jonathan
Inhibitory Plasticity: From Molecules to Computation and Beyond
title Inhibitory Plasticity: From Molecules to Computation and Beyond
title_full Inhibitory Plasticity: From Molecules to Computation and Beyond
title_fullStr Inhibitory Plasticity: From Molecules to Computation and Beyond
title_full_unstemmed Inhibitory Plasticity: From Molecules to Computation and Beyond
title_short Inhibitory Plasticity: From Molecules to Computation and Beyond
title_sort inhibitory plasticity: from molecules to computation and beyond
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7084224/
https://www.ncbi.nlm.nih.gov/pubmed/32155701
http://dx.doi.org/10.3390/ijms21051805
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