Stochastic transitions into silence cause noise correlations in cortical circuits.
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.
Nencki Institute of Experimental Biology, 02-093 Warsaw, Poland; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain;
Gabriela
G
Mochol
Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain;
Ainhoa
A
Hermoso-Mendizabal
Centre for Neuroscience and Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow G4 0RE, United Kingdom; and.
Shuzo
S
Sakata
UCL Institute of Neurology and UCL Department of Neuroscience, Physiology, and Pharmacology, University College London, London WC1E 6DE, United Kingdom.
Kenneth D
KD
Harris
Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; jrochav@clinic.ub.es.
Jaime
J
de la Rocha
D000161:Acoustic Stimulation; D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001303:Auditory Cortex / Q000502:physiology*; D005071:Evoked Potentials / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D009622:Noise; D017207:Rats, Sprague-Dawley; D013269:Stochastic Processes
auditory cortex; brain state; neuronal variability; noise correlations; stochastic network dynamics