Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit.
dc.contributor.author | Ponzi, Adam | |
dc.contributor.author | Dura-Bernal, Salvador | |
dc.contributor.author | Migliore, Michele | |
dc.date.accessioned | 2023-03-29T16:43:22Z | |
dc.date.available | 2023-03-29T16:43:22Z | |
dc.date.issued | 2023-03-23 | |
dc.identifier.citation | Ponzi A, Dura-Bernal S, Migliore M. Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit. PLoS Comput Biol. 2023 Mar 23;19(3):e1010942. doi: 10.1371/journal.pcbi.1010942. Epub ahead of print. PMID: 36952558. | en_US |
dc.identifier.eissn | 1553-7358 | |
dc.identifier.doi | 10.1371/journal.pcbi.1010942 | |
dc.identifier.pmid | 36952558 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12648/8548 | |
dc.description.abstract | Phase amplitude coupling (PAC) between slow and fast oscillations is found throughout the brain and plays important functional roles. Its neural origin remains unclear. Experimental findings are often puzzling and sometimes contradictory. Most computational models rely on pairs of pacemaker neurons or neural populations tuned at different frequencies to produce PAC. Here, using a data-driven model of a hippocampal microcircuit, we demonstrate that PAC can naturally emerge from a single feedback mechanism involving an inhibitory and excitatory neuron population, which interplay to generate theta frequency periodic bursts of higher frequency gamma. The model suggests the conditions under which a CA1 microcircuit can operate to elicit theta-gamma PAC, and highlights the modulatory role of OLM and PVBC cells, recurrent connectivity, and short term synaptic plasticity. Surprisingly, the results suggest the experimentally testable prediction that the generation of the slow population oscillation requires the fast one and cannot occur without it. | |
dc.language.iso | en | en_US |
dc.relation.url | https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010942 | en_US |
dc.rights | Copyright: © 2023 Ponzi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit. | en_US |
dc.type | Article/Review | en_US |
dc.source.journaltitle | PLoS computational biology | en_US |
dc.source.volume | 19 | |
dc.source.issue | 3 | |
dc.source.beginpage | e1010942 | |
dc.source.endpage | ||
dc.source.country | United States | |
dc.description.version | VoR | en_US |
refterms.dateFOA | 2023-03-29T16:43:23Z | |
html.description.abstract | Phase amplitude coupling (PAC) between slow and fast oscillations is found throughout the brain and plays important functional roles. Its neural origin remains unclear. Experimental findings are often puzzling and sometimes contradictory. Most computational models rely on pairs of pacemaker neurons or neural populations tuned at different frequencies to produce PAC. Here, using a data-driven model of a hippocampal microcircuit, we demonstrate that PAC can naturally emerge from a single feedback mechanism involving an inhibitory and excitatory neuron population, which interplay to generate theta frequency periodic bursts of higher frequency gamma. The model suggests the conditions under which a CA1 microcircuit can operate to elicit theta-gamma PAC, and highlights the modulatory role of OLM and PVBC cells, recurrent connectivity, and short term synaptic plasticity. Surprisingly, the results suggest the experimentally testable prediction that the generation of the slow population oscillation requires the fast one and cannot occur without it. | |
dc.description.institution | SUNY Downstate | en_US |
dc.description.department | Physiology and Pharmacology | en_US |
dc.description.degreelevel | N/A | en_US |
dc.identifier.journal | PLoS computational biology |