Neural modes in motor cortex cycle over fast timescales

The embedding of low-dimensional latent states in the activity of large neuron populations has become a tenet of systems neuroscience. Despite the stability of these latent representations over time, 1 the underlying activity of individual neurons is known to change both within experimental sessions and across days; 2 yet, less attention has been devoted to changes in the coordinated activity of neuron populations on short timescales, particularly under conditions where networks must adapt quickly (e.g., during learning or after injury). To investigate, patterns of individual neuron contributions to population state dimensions in motor cortex were tracked over short blocks of repeated reaching trials. The number of distinct encoding patterns was consistently less than the typical dimensionality reported for motor cortex. Although the neuron population state space and dynamics were effectively conserved, these underlying encoding patterns changed in two ways: fast switches among themselves, as well as slow modifications over time. To explore whether these two drift timescales shared a common physiological mechanism, we analyzed the response of motor cortex to a causal perturbation. Direct electrical current was passed through two recording electrodes to terminate a small number of neurons, 3-6 which evoked drift over both fast and slow timescales, both together and independently. While changes in fast switch rates were not necessarily associated with behavioral deficits, a significant increase in slow drift was accompanied by a decrease in behavioral performance. Together, these results reveal an additional timescale of drift in correlated population activity that could help guide the discovery of cellular and network mechanisms responsible for the maintenance, (re)learning, and recovery of low-dimensional structure in neuron populations.