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Plasticity of Persistent Activity and Its Constraints
Stimulus information is maintained in working memory by action potentials that persist after the stimulus is no longer physically present. The prefrontal cortex is a critical brain area that maintains such persistent activity due to an intrinsic network with unique synaptic connectivity, NMDA recept...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247814/ https://www.ncbi.nlm.nih.gov/pubmed/32528254 http://dx.doi.org/10.3389/fncir.2020.00015 |
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author | Li, Sihai Zhou, Xin Constantinidis, Christos Qi, Xue-Lian |
author_facet | Li, Sihai Zhou, Xin Constantinidis, Christos Qi, Xue-Lian |
author_sort | Li, Sihai |
collection | PubMed |
description | Stimulus information is maintained in working memory by action potentials that persist after the stimulus is no longer physically present. The prefrontal cortex is a critical brain area that maintains such persistent activity due to an intrinsic network with unique synaptic connectivity, NMDA receptors, and interneuron types. Persistent activity can be highly plastic depending on task demands but it also appears in naïve subjects, not trained or required to perform a task at all. Here, we review what aspects of persistent activity remain constant and what factors can modify it, focusing primarily on neurophysiological results from non-human primate studies. Changes in persistent activity are constrained by anatomical location, with more ventral and more anterior prefrontal areas exhibiting the greatest capacity for plasticity, as opposed to posterior and dorsal areas, which change relatively little with training. Learning to perform a cognitive task for the first time, further practicing the task, and switching between learned tasks can modify persistent activity. The ability of the prefrontal cortex to generate persistent activity also depends on age, with changes noted between adolescence, adulthood, and old age. Mean firing rates, variability and correlation of persistent discharges, but also time-varying firing rate dynamics are altered by these factors. Plastic changes in the strength of intrinsic network connections can be revealed by the analysis of synchronous spiking between neurons. These results are essential for understanding how the prefrontal cortex mediates working memory and intelligent behavior. |
format | Online Article Text |
id | pubmed-7247814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72478142020-06-10 Plasticity of Persistent Activity and Its Constraints Li, Sihai Zhou, Xin Constantinidis, Christos Qi, Xue-Lian Front Neural Circuits Neuroscience Stimulus information is maintained in working memory by action potentials that persist after the stimulus is no longer physically present. The prefrontal cortex is a critical brain area that maintains such persistent activity due to an intrinsic network with unique synaptic connectivity, NMDA receptors, and interneuron types. Persistent activity can be highly plastic depending on task demands but it also appears in naïve subjects, not trained or required to perform a task at all. Here, we review what aspects of persistent activity remain constant and what factors can modify it, focusing primarily on neurophysiological results from non-human primate studies. Changes in persistent activity are constrained by anatomical location, with more ventral and more anterior prefrontal areas exhibiting the greatest capacity for plasticity, as opposed to posterior and dorsal areas, which change relatively little with training. Learning to perform a cognitive task for the first time, further practicing the task, and switching between learned tasks can modify persistent activity. The ability of the prefrontal cortex to generate persistent activity also depends on age, with changes noted between adolescence, adulthood, and old age. Mean firing rates, variability and correlation of persistent discharges, but also time-varying firing rate dynamics are altered by these factors. Plastic changes in the strength of intrinsic network connections can be revealed by the analysis of synchronous spiking between neurons. These results are essential for understanding how the prefrontal cortex mediates working memory and intelligent behavior. Frontiers Media S.A. 2020-05-07 /pmc/articles/PMC7247814/ /pubmed/32528254 http://dx.doi.org/10.3389/fncir.2020.00015 Text en Copyright © 2020 Li, Zhou, Constantinidis and Qi. 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 Li, Sihai Zhou, Xin Constantinidis, Christos Qi, Xue-Lian Plasticity of Persistent Activity and Its Constraints |
title | Plasticity of Persistent Activity and Its Constraints |
title_full | Plasticity of Persistent Activity and Its Constraints |
title_fullStr | Plasticity of Persistent Activity and Its Constraints |
title_full_unstemmed | Plasticity of Persistent Activity and Its Constraints |
title_short | Plasticity of Persistent Activity and Its Constraints |
title_sort | plasticity of persistent activity and its constraints |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247814/ https://www.ncbi.nlm.nih.gov/pubmed/32528254 http://dx.doi.org/10.3389/fncir.2020.00015 |
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