Volitional stopping is preceded by a transient motor cortex EEG beta oscillation

EEG beta (15-30 Hz) oscillations undergo power modulations during volitional movements. The prevailing view is that beta oscillations are involved in inhibitory control, but their timing relative to movement cancellation is highly variable across studies. This variability has hindered their usefulness for brain-machine interfaces and constrained understanding their role in Parkinson’s disease. The variability arises from use of the stop-signal task, in which movement cancellation time is covert. We recorded 32-electrode cortex-wide EEG along with the velocity of a treadmill while head-fixed rats stopped in-progress running. A single beta oscillation cycle occurred in the left motor cortex around 200 msec before movement cancellation with consistent across-trial timing. Using information theory, we show that beta power was informative about velocity 200 msec in the future, but only during planning to stop. By introducing artificial temporal jitter to mimic the estimation of a covert stopping time used in prior work, we show that this predictive brain-action relationship fails with even small jitter. Finally, we use machine learning methods to show that, despite EEG beta oscillations being a clear neural correlate of stopping, it has limited utility for real-time action decoding. Our work suggests a new conceptual model for neural control of overt action stopping.