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A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits
Computational models of neural circuits with varying levels of biophysical detail have been generated in pursuit of an underlying mechanism explaining the ubiquitous hippocampal theta rhythm. However, within the theta rhythm are at least two types with distinct frequencies associated with different...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097141/ https://www.ncbi.nlm.nih.gov/pubmed/33967702 http://dx.doi.org/10.3389/fncir.2021.643360 |
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author | Skinner, Frances K. Rich, Scott Lunyov, Anton R. Lefebvre, Jeremie Chatzikalymniou, Alexandra P. |
author_facet | Skinner, Frances K. Rich, Scott Lunyov, Anton R. Lefebvre, Jeremie Chatzikalymniou, Alexandra P. |
author_sort | Skinner, Frances K. |
collection | PubMed |
description | Computational models of neural circuits with varying levels of biophysical detail have been generated in pursuit of an underlying mechanism explaining the ubiquitous hippocampal theta rhythm. However, within the theta rhythm are at least two types with distinct frequencies associated with different behavioral states, an aspect that must be considered in pursuit of these mechanistic explanations. Here, using our previously developed excitatory-inhibitory network models that generate theta rhythms, we investigate the robustness of theta generation to intrinsic neuronal variability by building a database of heterogeneous excitatory cells and implementing them in our microcircuit model. We specifically investigate the impact of three key “building block” features of the excitatory cell model that underlie our model design: these cells' rheobase, their capacity for post-inhibitory rebound, and their spike-frequency adaptation. We show that theta rhythms at various frequencies can arise dependent upon the combination of these building block features, and we find that the speed of these oscillations are dependent upon the excitatory cells' response to inhibitory drive, as encapsulated by their phase response curves. Taken together, these findings support a hypothesis for theta frequency control that includes two aspects: (i) an internal mechanism that stems from the building block features of excitatory cell dynamics; (ii) an external mechanism that we describe as “inhibition-based tuning” of excitatory cell firing. We propose that these mechanisms control theta rhythm frequencies and underlie their robustness. |
format | Online Article Text |
id | pubmed-8097141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80971412021-05-06 A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits Skinner, Frances K. Rich, Scott Lunyov, Anton R. Lefebvre, Jeremie Chatzikalymniou, Alexandra P. Front Neural Circuits Neuroscience Computational models of neural circuits with varying levels of biophysical detail have been generated in pursuit of an underlying mechanism explaining the ubiquitous hippocampal theta rhythm. However, within the theta rhythm are at least two types with distinct frequencies associated with different behavioral states, an aspect that must be considered in pursuit of these mechanistic explanations. Here, using our previously developed excitatory-inhibitory network models that generate theta rhythms, we investigate the robustness of theta generation to intrinsic neuronal variability by building a database of heterogeneous excitatory cells and implementing them in our microcircuit model. We specifically investigate the impact of three key “building block” features of the excitatory cell model that underlie our model design: these cells' rheobase, their capacity for post-inhibitory rebound, and their spike-frequency adaptation. We show that theta rhythms at various frequencies can arise dependent upon the combination of these building block features, and we find that the speed of these oscillations are dependent upon the excitatory cells' response to inhibitory drive, as encapsulated by their phase response curves. Taken together, these findings support a hypothesis for theta frequency control that includes two aspects: (i) an internal mechanism that stems from the building block features of excitatory cell dynamics; (ii) an external mechanism that we describe as “inhibition-based tuning” of excitatory cell firing. We propose that these mechanisms control theta rhythm frequencies and underlie their robustness. Frontiers Media S.A. 2021-04-21 /pmc/articles/PMC8097141/ /pubmed/33967702 http://dx.doi.org/10.3389/fncir.2021.643360 Text en Copyright © 2021 Skinner, Rich, Lunyov, Lefebvre and Chatzikalymniou. 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 Skinner, Frances K. Rich, Scott Lunyov, Anton R. Lefebvre, Jeremie Chatzikalymniou, Alexandra P. A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits |
title | A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits |
title_full | A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits |
title_fullStr | A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits |
title_full_unstemmed | A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits |
title_short | A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits |
title_sort | hypothesis for theta rhythm frequency control in ca1 microcircuits |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097141/ https://www.ncbi.nlm.nih.gov/pubmed/33967702 http://dx.doi.org/10.3389/fncir.2021.643360 |
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