Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Author:

Zeraati RoxanaORCID,Shi Yan-LiangORCID,Steinmetz Nicholas A.ORCID,Gieselmann Marc A.,Thiele Alexander,Moore TirinORCID,Levina AnnaORCID,Engel Tatiana A.ORCID

Abstract

AbstractIntrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.

Funder

Alexander von Humboldt-Stiftung

Bernstein Center for Computational Neuroscience Tübingen

Alfred P. Sloan Foundation

U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse

RCUK | Medical Research Council

Pershing Square Foundation

U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry,Multidisciplinary

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