Network dynamics underlying activity-timescale differences between cortical regions

Network-level dynamics are thought to be central to computation in the cerebral cortex. Yet, how these dynamics differ across areas remains poorly understood. We leveraged an intrinsic property of cortical regions to tackle this problem — the timescales over which they spontaneously sustain activity. We first co-registered functional and spatial transcriptomics datasets to show that timescales across the mouse cortex are predicted by many transcript categories, including those that regulate circuit wiring. Next, we used simultaneous two-photon imaging and optogenetics in mice to ask how these putative differences in connectivity lead to distinct network responses to brief, focal excitatory input to a short-timescale visual area, VISp, and a long-timescale frontal area, MOs. MOs neurons were more likely to respond to photostimulation of their neighbors. Moreover, the evoked dynamics of the overall network were much longer lasting in MOs than VISp, due to the more prevalent recruitment of late-responding neurons, which formed reliable activity sequences. Overall, our findings show that, beyond single-neuron timescales, different cortical areas are distinctly wired to sustain input over varying time windows via network dynamics, with important implications for our understanding of cortical computation.