Predicting Reaction Time from the Neural State Space of the Premotor and Parietal Grasping Network

Abstract

Neural networks of the brain involved in the planning and execution of grasping movements are not fully understood. The network formed by macaque anterior intraparietal area (AIP) and hand area (F5) of the ventral premotor cortex is implicated strongly in the generation of grasping movements. However, the differential role of each area in this frontoparietal network is unclear. We recorded spiking activity from many electrodes in parallel in AIP and F5 while three macaque monkeys (Macaca mulatta) performed a delayed grasping task. By analyzing neural population activity during action preparation, we found that state space analysis of simultaneously recorded units is significantly more predictive of subsequent reaction times (RTs) than traditional methods. Furthermore, because we observed a wide variety of individual unit characteristics, we developed the sign-corrected average rate (SCAR) method of neural population averaging. The SCAR method was able to explain at least as much variance in RT overall as state space methods. Overall, F5 activity predicted RT (18% variance explained) significantly better than AIP (6%). The SCAR methods provides a straightforward interpretation of population activity, although other state space methods could provide richer descriptions of population dynamics. Together, these results lend support to the differential role of the parietal and frontal cortices in preparation for grasping, suggesting that variability in preparatory activity in F5 has a more potent effect on trial-to-trial RT variability than AIP.

Individual Differences in Resting Corticospinal Excitability Are Correlated with Reaction Time and GABA Content in Motor Cortex

“…We assume that RTs and MEPs are composite measures, consisting of transient, staterelated changes in cortical dynamics that occur on top of relatively invariant, individual differences. Previous work with TMS has clearly established that MEPs and, to some degree, RT, are highly sensitive to transient changes in motor system excitability (Starr et al, 1988;Leocani et al, 2000;Greenhouse et al, 2015b;Michaels et al, 2015;Hammer et al, 2016). Here, we demonstrate that RT and MEP measurements exhibit stable individual differences.…”

Physiological Markers of Motor Inhibition during Human Behavior

“…This increase is, of course, the classic effect observed in neurophysiological studies with non-human primates. Indeed, activation during response preparation allows the forthcoming response to be decoded from the activity of many cortical and subcortical areas of the motor pathway during delay periods [109–111]. Correspondingly, paired-pulse TMS protocols reveal local increases in cortical excitability in human M1: Intracortical inhibition is attenuated and intracortical facilitation is enhanced during preparatory periods, even though the overall excitability state of the corticospinal pathway associated with that response is suppressed [84, 112, 113].…”

Flexible sensorimotor computations through rapid reconfiguration of cortical dynamics

“…See below description for calculation of for shortest and longest t s . ( C ) Prediction 2 ( P 2 ): deviations along trajectories should influence the time it takes for activity to reach the Go state and should therefore influence t p (Afshar et al 2011;Michaels et al 2015) . If P 2 is correct, then should be ahead of .…”