Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex

Yan-Liang Shi, Nicholas A. Steinmetz, Tirin Moore, Kwabena Boahen and Tatiana A. Engel ()
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Yan-Liang Shi: Cold Spring Harbor Laboratory
Nicholas A. Steinmetz: University of Washington
Tirin Moore: Stanford University
Kwabena Boahen: Stanford University
Tatiana A. Engel: Cold Spring Harbor Laboratory

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Correlated activity fluctuations in the neocortex influence sensory responses and behavior. Neural correlations reflect anatomical connectivity but also change dynamically with cognitive states such as attention. Yet, the network mechanisms defining the population structure of correlations remain unknown. We measured correlations within columns in the visual cortex. We show that the magnitude of correlations, their attentional modulation, and dependence on lateral distance are explained by columnar On-Off dynamics, which are synchronous activity fluctuations reflecting cortical state. We developed a network model in which the On-Off dynamics propagate across nearby columns generating spatial correlations with the extent controlled by attentional inputs. This mechanism, unlike previous proposals, predicts spatially non-uniform changes in correlations during attention. We confirm this prediction in our columnar recordings by showing that in superficial layers the largest changes in correlations occur at intermediate lateral distances. Our results reveal how spatially structured patterns of correlated variability emerge through interactions of cortical state dynamics, anatomical connectivity, and attention.

Date: 2022
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DOI: 10.1038/s41467-021-27724-4

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