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

Abstract

Neural activity fluctuates endogenously on timescales varying across the neocortex. The variation in these intrinsic timescales relates to the functional specialization of cortical areas and their involvement in the temporal integration of information. Yet, it is unknown whether the timescales can adjust rapidly and selectively to the demands of a cognitive task. We measured intrinsic timescales of local spiking activity within columns of area V4 while monkeys performed spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales---fast and slow---and the slow timescale increased when monkeys attended to the receptive fields location. A recurrent network model shows that multiple timescales in local dynamics arise from spatial connectivity mimicking vertical and horizontal interactions in visual cortex and that slow timescales increase with the efficacy of recurrent interactions. Our results reveal that targeted neural populations integrate information over variable timescales following the demands of a cognitive task and propose an underlying network mechanism.

Multiple timescales of sensory-evidence accumulation across the dorsal cortex

“…This is reminiscent of the findings that cortical areas display a hierarchy of intrinsic timescales, such that primary sensory areas tend to integrate over shorter time windows than frontal and other association areas ( Chaudhuri et al, 2015 ; Hasson et al, 2008 ; Murray et al, 2014 ; Runyan et al, 2017 ). While these are thought to arise in part from intrinsic cellular and circuit properties such as channel and receptor expression, amount of recurrent connectivity, and relative proportions of inhibitory interneuron subtypes ( Chaudhuri et al, 2015 ; Duarte et al, 2017 ; Fulcher et al, 2019 ; Gao et al, 2020 ; Wang, 2020 ), they appear to be modulated by task demands ( Gao et al, 2020 ; Ito et al, 2020 ; Zeraati et al, 2021 ). Thus, to confirm whether this timescale hierarchy exists in the mouse cortex during performance of the accumulating-towers task, we reanalyzed previously published data consisting of mesoscale widefield Ca 2+ imaging of the dorsal cortex through the intact cleared skull of mice expressing the Ca 2+ indicator GCaMP6f in excitatory neurons ( Figure 4A , Emx1-Ai93 triple transgenics, n=6, 25 sessions) ( Pinto et al, 2019 ).…”

Internally generated population activity in cortical networks hinders information transmission

“…In the regime of wave dynamics, network activity shows gamma rhythms (25 to 50 Hz) and, on average, positive correlations across all distances. Recordings from visual cortex have found fluctuations around the 70- to 150-ms time scale ( 59 , 60 ) and, on average, positive correlations across long distance ( 36 ), which is more consistent with the wave dynamics regime.…”

“…S3B). We note that networks in this regime lack fluctuations on the slow time scale as measured in the visual cortex [around 70 to 150 ms; ( 59 , 60 )]. Furthermore, the global fluctuations in the spontaneous activities of the spiking neuron network are largely suppressed with more input to the inhibitory neurons ( Fig.…”

A flexible Bayesian framework for unbiased estimation of timescales

“…The variation of timescales across brain areas reflects the functional hierarchy in the neocortex and areal differences in temporal integration of information [3, 20–22], while aberrant timescales were associated with autism [23]. Precise estimation methods are necessary to detect changes in timescales during cognitive processes such as attention [24]. Estimated timescales are also used to determine the operating regime of the dynamics, e.g., how close the system is to a critical point [25], which can reveal general principles organizing the collective behavior of complex systems such as the brain [26–28].…”