Neural correlates of instructed movements
Recent results suggest that movement is widely and largely indiscriminately represented across the cortex, including in areas whose contribution to the specification of those movements is not apparent. Because the outcome of task-related computations is produced through instructed movements, the ubiquity of movement-related neural signals makes it difficult to interpret and quantify the potential causal contribution of these signals towards a specific behavior. In addition to experiments which directly perturb neural activity– which are still somewhat coarse and difficult to interpret — one can gain insight into the functional role of a particular neural correlate by examining its temporal relationship with the corresponding instructed movement. We have developed a simple and robust regression-based algorithm that fits the moment-to-moment lag between ongoing neural population activity and ongoing behavioral signals. Using this method, we’ve provided evidence that neural activity in the mouse prefrontal cortex has a flexible temporal relationship with instructed movement — in this case speed in a treadmill — with reversals in the sign of the lag between neural activity and speed. Such reversals are consistent with prefrontal activity having a putative causal role (speed lags neurons) at moments where changes in speed are “freely” chosen by the mouse, and with speed having a putative causal role on neural activity (neurons lag speed) when changes in speed are externally instructed.