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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7084224 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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