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Attentional modulation of intrinsic timescales in visual cortex and spatial networks
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\textemdashfast and slow\textemdashand 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.
@misc{item_3321592, title = {{Attentional modulation of intrinsic timescales in visual cortex and spatial networks}}, 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\textemdashfast and slow\textemdashand 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.}, year = {2021}, slug = {item_3321592}, author = {Zeraati, R and Shi, Y-L and Steinmetz, NA and Gieselmann, MA and Thiele, A and Moore, T and Levina, A and Engel, TA} }