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Phase relations of interneuronal activity relative to theta rhythm

The theta rhythm plays a crucial role in synchronizing neural activity during attention and memory processes. However, the mechanisms behind the formation of neural activity during theta rhythm generation remain unknown. To address this, we propose a mathematical model that explains the distribution...

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Detalles Bibliográficos
Autor principal: Mysin, Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358363/
https://www.ncbi.nlm.nih.gov/pubmed/37484208
http://dx.doi.org/10.3389/fncir.2023.1198573
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author Mysin, Ivan
author_facet Mysin, Ivan
author_sort Mysin, Ivan
collection PubMed
description The theta rhythm plays a crucial role in synchronizing neural activity during attention and memory processes. However, the mechanisms behind the formation of neural activity during theta rhythm generation remain unknown. To address this, we propose a mathematical model that explains the distribution of interneurons in the CA1 field during the theta rhythm phase. Our model consists of a network of seven types of interneurons in the CA1 field that receive inputs from the CA3 field, entorhinal cortex, and local pyramidal neurons in the CA1 field. By adjusting the parameters of the connections in the model. We demonstrate that it is possible to replicate the experimentally observed phase relations between interneurons and the theta rhythm. Our model predicts that populations of interneurons receive unimodal excitation and inhibition with coinciding peaks, and that excitation dominates to determine the firing dynamics of interneurons.
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spelling pubmed-103583632023-07-21 Phase relations of interneuronal activity relative to theta rhythm Mysin, Ivan Front Neural Circuits Neuroscience The theta rhythm plays a crucial role in synchronizing neural activity during attention and memory processes. However, the mechanisms behind the formation of neural activity during theta rhythm generation remain unknown. To address this, we propose a mathematical model that explains the distribution of interneurons in the CA1 field during the theta rhythm phase. Our model consists of a network of seven types of interneurons in the CA1 field that receive inputs from the CA3 field, entorhinal cortex, and local pyramidal neurons in the CA1 field. By adjusting the parameters of the connections in the model. We demonstrate that it is possible to replicate the experimentally observed phase relations between interneurons and the theta rhythm. Our model predicts that populations of interneurons receive unimodal excitation and inhibition with coinciding peaks, and that excitation dominates to determine the firing dynamics of interneurons. Frontiers Media S.A. 2023-07-06 /pmc/articles/PMC10358363/ /pubmed/37484208 http://dx.doi.org/10.3389/fncir.2023.1198573 Text en Copyright © 2023 Mysin. https://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
Mysin, Ivan
Phase relations of interneuronal activity relative to theta rhythm
title Phase relations of interneuronal activity relative to theta rhythm
title_full Phase relations of interneuronal activity relative to theta rhythm
title_fullStr Phase relations of interneuronal activity relative to theta rhythm
title_full_unstemmed Phase relations of interneuronal activity relative to theta rhythm
title_short Phase relations of interneuronal activity relative to theta rhythm
title_sort phase relations of interneuronal activity relative to theta rhythm
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358363/
https://www.ncbi.nlm.nih.gov/pubmed/37484208
http://dx.doi.org/10.3389/fncir.2023.1198573
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