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Biased competition in the absence of input bias revealed through corticostriatal computation

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Biased competition in the absence of input bias revealed through corticostriatal computation

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dc.contributor.author Ardid-Ramírez, Joan Salvador es_ES
dc.contributor.author Sherfey, Jason S. es_ES
dc.contributor.author McCarthy, Michelle M. es_ES
dc.contributor.author Hass, Joachim es_ES
dc.contributor.author Pittman-Polletta, Benjamin R. es_ES
dc.contributor.author Kopell, Nancy es_ES
dc.date.accessioned 2021-09-03T03:34:26Z
dc.date.available 2021-09-03T03:34:26Z
dc.date.issued 2019-04-23 es_ES
dc.identifier.issn 0027-8424 es_ES
dc.identifier.uri http://hdl.handle.net/10251/171332
dc.description.abstract [EN] Classical accounts of biased competition require an input bias to resolve the competition between neuronal ensembles driving downstream processing. However, flexible and reliable selection of behaviorally relevant ensembles can occur with unbiased stimulation: striatal D1 and D2 spiny projection neurons (SPNs) receive balanced cortical input, yet their activity determines the choice between GO and NO-GO pathways in the basal ganglia. We here present a corticostriatal model identifying three mechanisms that rely on physiological asymmetries to effect rate- and time-coded biased competition in the presence of balanced inputs. First, tonic input strength determines which one of the two SPN phenotypes exhibits a higher mean firing rate. Second, low-strength oscillatory inputs induce higher firing rate in D2 SPNs but higher coherence between D1 SPNs. Third, high-strength inputs oscillating at distinct frequencies can preferentially activate D1 or D2 SPN populations. Of these mechanisms, only the latter accommodates observed rhythmic activity supporting rule-based decision making in prefrontal cortex es_ES
dc.description.sponsorship We thank T. Womelsdorf for helpful suggestions on an earlier version of the manuscript. We also thank the two reviewers for the constructive comments that enhanced the quality of the manuscript. In particular, their question regarding the resonant properties of SPNs under distinct mean input helped us to uncover how the resonance of D2 SPNs shifts in frequency space (Fig. 3E). Our research was supported by the Army Research Office (ARO) Grant W911NF-12-R-0012-02 (to N.K.). Additionally, S.A. and N.K. were supported by NSF Grant DMS-1042134, and M.M.M. was supported by the Collaborative Research in Computational Neuroscience (CRCNS) NIH Grant CRCNS 1R01N5081716 es_ES
dc.language Inglés es_ES
dc.publisher Proceedings of the National Academy of Sciences es_ES
dc.relation.ispartof Proceedings of the National Academy of Sciences es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Rule-based decisions es_ES
dc.subject Prefrontal cortex es_ES
dc.subject Brain rhythms es_ES
dc.subject Neural circuit modeling es_ES
dc.subject Spiny projection neurons es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Biased competition in the absence of input bias revealed through corticostriatal computation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1073/pnas.1812535116 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/NIH//1R01N5081716/ 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.rights.accessRights Cerrado 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 Ardid-Ramírez, JS.; Sherfey, JS.; Mccarthy, MM.; Hass, J.; Pittman-Polletta, BR.; Kopell, N. (2019). Biased competition in the absence of input bias revealed through corticostriatal computation. Proceedings of the National Academy of Sciences. 116(17):8564-8569. https://doi.org/10.1073/pnas.1812535116 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1073/pnas.1812535116 es_ES
dc.description.upvformatpinicio 8564 es_ES
dc.description.upvformatpfin 8569 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 116 es_ES
dc.description.issue 17 es_ES
dc.identifier.pmid 30962383 es_ES
dc.identifier.pmcid PMC6486766 es_ES
dc.relation.pasarela S\434965 es_ES
dc.contributor.funder Army Research Office, EEUU es_ES
dc.contributor.funder National Science Foundation, EEUU es_ES
dc.contributor.funder National Institutes of Health, EEUU es_ES
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