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

Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity.
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DOI:
10.1038/s41467-023-37613-7
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发表时间:
2023-04-03
影响因子:
16.6
通讯作者:
Engel, Tatiana A.
Engel, Tatiana A.
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Zeraati, Roxana;Shi, Yan-Liang;Steinmetz, Nicholas A.;Gieselmann, Marc A.;Thiele, Alexander;Moore, Tirin;Levina, Anna;Engel, Tatiana A.

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Intrinsic 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. Not much is known about how intrinsic timescales, which characterize the dynamics of endogenous fluctuations in neural activity, change during cognitive tasks. Here, the authors show that intrinsic timescales of neural activity in the primate visual cortex change during spatial attention. Experimental data were best explained by a network model in which timescales arise from spatially arranged connectivity.
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