Stochastic transitions into silence cause noise correlations in cortical circuits
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Mochol, Gabriela
- dc.contributor.author Hermoso Mendizábal, Ainhoa
- dc.contributor.author Sakata, Shuzo
- dc.contributor.author Harris, Kenneth D.
- dc.contributor.author De la Rocha, Jaime
- dc.date.accessioned 2018-12-20T17:48:47Z
- dc.date.available 2018-12-20T17:48:47Z
- dc.date.issued 2015
- dc.description.abstract The spiking activity of cortical neurons is highly variable. This variability is generally correlated among nearby neurons, an effect commonly interpreted to reflect the coactivation of neurons due to anatomically shared inputs. Recent findings, however, indicate that correlations can be dynamically modulated, suggesting that the underlying mechanisms are not well understood. Here, we investigate the hypothesis that correlations are dominated by neuronal coinactivation: the occurrence of brief silent periods during which all neurons in the local network stop firing. We recorded spiking activity from large populations of neurons in the auditory cortex of anesthetized rats across different brain states. During spontaneous activity, the reduction of correlation accompanying brain state desynchronization was largely explained by a decrease in the density of the silent periods. The presentation of a stimulus caused an initial drop of correlations followed by a rebound, a time course that was mimicked by the instantaneous silence density. We built a rate network model with fluctuation-driven transitions between a silent and an active attractor and assumed that neurons fired Poisson spike trains with a rate following the model dynamics. Variations of the network external input altered the transition rate into the silent attractor and reproduced the relation between correlation and silence density found in the data, both in spontaneous and evoked conditions. This suggests that the observed changes in correlation, occurring gradually with brain state variations or abruptly with sensory stimulation, are due to changes in the likeliness of the microcircuit to transiently cease firing.en
- dc.description.sponsorship This work was supported by the Polish Ministry of Science and Higher Education “Mobility Plus” Program Grant 641/MOB/2011/0 (to G.M.); the Spanish Ministry of Economy and Competitiveness together with the European Regional Development Fund Grants BES-2011-049131 (to A.H.-M.), and SAF2010-15730, SAF2013-46717-R, and RYC-2009-04829 (to J.R.); European Union Marie Curie Grant IRG PIRG07-GA-2010-268382 (to J.R.); and Wellcome Trust Grant 095668 (to K.D.H.).en
- dc.format.mimetype application/pdf
- dc.identifier.citation Mochol G, Hermoso-Mendizabal A, Sakata S, Harris K.D, de la Rocha J. Stochastic transitions into silence cause noise correlations in cortical circuits. Proc Natl Acad Sci U S A. 2015;112(11):3529-34. DOI: 10.1073/pnas.1410509112
- dc.identifier.doi http://dx.doi.org/10.1073/pnas.1410509112
- dc.identifier.issn 0027-8424
- dc.identifier.uri http://hdl.handle.net/10230/36168
- dc.language.iso eng
- dc.publisher National Academy of Sciences
- dc.relation.ispartof Proceedings of the National Academy of Sciences of the United States of America. 2015;112(11):3529-34
- dc.rights © National Academy of Sciences. https://www.pnas.org/content/112/11/3529
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.subject.keyword Neuronal variabilityen
- dc.subject.keyword Noise correlationsen
- dc.subject.keyword Brain stateen
- dc.subject.keyword Auditory cortexen
- dc.subject.keyword Stochastic network dynamicsen
- dc.title Stochastic transitions into silence cause noise correlations in cortical circuits
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/acceptedVersion