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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-04-01
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| Series: | Frontiers in Neural Circuits |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fncir.2021.643360/full |
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| author | Frances K. Skinner Frances K. Skinner Frances K. Skinner Scott Rich Anton R. Lunyov Jeremie Lefebvre Alexandra P. Chatzikalymniou Alexandra P. Chatzikalymniou |
| author_facet | Frances K. Skinner Frances K. Skinner Frances K. Skinner Scott Rich Anton R. Lunyov Jeremie Lefebvre Alexandra P. Chatzikalymniou Alexandra P. Chatzikalymniou |
| author_sort | Frances K. Skinner |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T21:11:43Z |
| format | Article |
| id | doaj.art-8e5ee882ffa74d53b2e4a984b0d31488 |
| institution | Directory Open Access Journal |
| issn | 1662-5110 |
| language | English |
| last_indexed | 2024-12-14T21:11:43Z |
| publishDate | 2021-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neural Circuits |
| spelling | doaj.art-8e5ee882ffa74d53b2e4a984b0d314882022-12-21T22:47:13ZengFrontiers Media S.A.Frontiers in Neural Circuits1662-51102021-04-011510.3389/fncir.2021.643360643360A Hypothesis for Theta Rhythm Frequency Control in CA1 MicrocircuitsFrances K. Skinner0Frances K. Skinner1Frances K. Skinner2Scott Rich3Anton R. Lunyov4Jeremie Lefebvre5Alexandra P. Chatzikalymniou6Alexandra P. Chatzikalymniou7Division of Clinical and Computational Neuroscience, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, ON, CanadaDepartment of Medicine (Neurology), University of Toronto, Toronto, ON, CanadaDepartment of Physiology, University of Toronto, Toronto, ON, CanadaDivision of Clinical and Computational Neuroscience, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, ON, CanadaDivision of Clinical and Computational Neuroscience, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, ON, CanadaDivision of Clinical and Computational Neuroscience, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, ON, CanadaDivision of Clinical and Computational Neuroscience, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, ON, CanadaDepartment of Physiology, University of Toronto, Toronto, ON, CanadaComputational 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.https://www.frontiersin.org/articles/10.3389/fncir.2021.643360/fulltheta rhythmtheta oscillationhippocampusinhibitionnetworkmicrocircuit |
| spellingShingle | Frances K. Skinner Frances K. Skinner Frances K. Skinner Scott Rich Anton R. Lunyov Jeremie Lefebvre Alexandra P. Chatzikalymniou Alexandra P. Chatzikalymniou A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits Frontiers in Neural Circuits theta rhythm theta oscillation hippocampus inhibition network microcircuit |
| 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 | theta rhythm theta oscillation hippocampus inhibition network microcircuit |
| url | https://www.frontiersin.org/articles/10.3389/fncir.2021.643360/full |
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