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Flexible resonance in prefrontal networks with strong feedback inhibition

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Flexible resonance in prefrontal networks with strong feedback inhibition

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dc.contributor.author Sherfey, Jason S. es_ES
dc.contributor.author Ardid-Ramírez, Joan Salvador es_ES
dc.contributor.author Hass, Joachim es_ES
dc.contributor.author Hasselmo, Michael E. es_ES
dc.contributor.author Kopell, Nancy J. es_ES
dc.date.accessioned 2021-06-09T03:32:05Z
dc.date.available 2021-06-09T03:32:05Z
dc.date.issued 2018-08-09 es_ES
dc.identifier.issn 1553-734X es_ES
dc.identifier.uri http://hdl.handle.net/10251/167608
dc.description.abstract [EN] Oscillations are ubiquitous features of brain dynamics that undergo task-related changes in synchrony, power, and frequency. The impact of those changes on target networks is poorly understood. In this work, we used a biophysically detailed model of prefrontal cortex (PFC) to explore the effects of varying the spike rate, synchrony, and waveform of strong oscillatory inputs on the behavior of cortical networks driven by them. Interacting populations of excitatory and inhibitory neurons with strong feedback inhibition are inhibition-based network oscillators that exhibit resonance (i.e., larger responses to preferred input frequencies). We quantified network responses in terms of mean firing rates and the population frequency of network oscillation; and characterized their behavior in terms of the natural response to asynchronous input and the resonant response to oscillatory inputs. We show that strong feedback inhibition causes the PFC to generate internal (natural) oscillations in the beta/gamma frequency range (>15 Hz) and to maximize principal cell spiking in response to external oscillations at slightly higher frequencies. Importantly, we found that the fastest oscillation frequency that can be relayed by the network maximizes local inhibition and is equal to a frequency even higher than that which maximizes the firing rate of excitatory cells; we call this phenomenon population frequency resonance. This form of resonance is shown to determine the optimal driving frequency for suppressing responses to asynchronous activity. Lastly, we demonstrate that the natural and resonant frequencies can be tuned by changes in neuronal excitability, the duration of feedback inhibition, and dynamic properties of the input. Our results predict that PFC networks are tuned for generating and selectively responding to beta- and gamma-rhythmic signals due to the natural and resonant properties of inhibition-based oscillators. They also suggest strategies for optimizing transcranial stimulation and using oscillatory networks in neuromorphic engineering. es_ES
dc.description.sponsorship This material is based upon research supported by the U. S. Army Research Office under award number ARO W911NF-12-R-0012-02 to N. K., the U. S. Office of Naval Research under award number ONR MURI N00014-16-1-2832 to M. H., and the National Science Foundation under award number NSF DMS-1042134 (Cognitive Rhythms Collaborative: A Discovery Network) to N. K. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. es_ES
dc.language Inglés es_ES
dc.publisher Public Library of Science es_ES
dc.relation.ispartof PLoS Computational Biology es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Flexible resonance in prefrontal networks with strong feedback inhibition es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1371/journal.pcbi.1006357 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ARO//W911NF-12-R-0012-02/US/Event-Driven Game Theory for Predicting Dynamical Systems/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSF//1042134/US/Cognitive Rhythms Collaborative: A Discovery Network/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ONR//N00014-16-1-2832/US/ONR MURI: Neural circuits underlying symbolic processing in primate cortex and basal ganglia/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres es_ES
dc.description.bibliographicCitation Sherfey, JS.; Ardid-Ramírez, JS.; Hass, J.; Hasselmo, ME.; Kopell, NJ. (2018). Flexible resonance in prefrontal networks with strong feedback inhibition. PLoS Computational Biology. 14(8). https://doi.org/10.1371/journal.pcbi.1006357 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1371/journal.pcbi.1006357 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 8 es_ES
dc.identifier.pmid 30091975 es_ES
dc.identifier.pmcid PMC6103521 es_ES
dc.relation.pasarela S\434973 es_ES
dc.contributor.funder Office of Naval Research es_ES
dc.contributor.funder Army Research Office, EEUU es_ES
dc.contributor.funder National Science Foundation, EEUU es_ES
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