Classic work using the stop-signal task has shown that humans can use inhibitory control to cancel already initiated movements. Subsequent work revealed that inhibitory control can be proactively recruited in anticipation of a potential stop-signal, thereby increasing the likelihood of successful movement cancellation. However, the exact neurophysiological effects of proactive inhibitory control on the motor system are still unclear. On the basis of classic views of sensorimotor β-band activity, as well as recent findings demonstrating the burst-like nature of this signal, we recently proposed that proactive inhibitory control is implemented by influencing the rate of sensorimotor β-bursts during movement initiation. Here, we directly tested this hypothesis using scalp EEG recordings of β-band activity in 41 healthy human adults during a bimanual RT task. By comparing motor responses made in two different contexts—during blocks with or without stop-signals—we found that premovement β-burst rates over both contralateral and ipsilateral sensorimotor areas were increased in stop-signal blocks compared to pure-go blocks. Moreover, the degree of this burst rate difference indexed the behavioral implementation of proactive inhibition (i.e., the degree of anticipatory response slowing in the stop-signal blocks). Finally, exploratory analyses showed that these condition differences were explained by a significant increase in β bursting that was already present during baseline period before the movement initiation signal. Together, this suggests that the strategic deployment of proactive inhibitory motor control is implemented by upregulating the tonic inhibition of the motor system, signified by increased sensorimotor β-bursting both before and after signals to initiate a movement.

The stop signal task (SST) is the gold standard experimental model of inhibitory control. However, neither SST condition–contrast (stop vs. go, successful vs. failed stop) purely operationalizes inhibition. Because stop trials include a second, infrequent signal, the stop versus go contrast confounds inhibition with attentional and stimulus processing demands. While this confound is controlled for in the successful versus failed stop contrast, the go process is systematically faster on failed stop trials, contaminating the contrast with a different noninhibitory confound. Here, we present an SST variant to address both confounds and evaluate putative neural indices of inhibition with these influences removed. In our variant, stop signals occurred on every trial, equating the noninhibitory demands of the stop versus go contrast. To entice participants to respond despite the impending stop signals, responses produced before stop signals were rewarded. This also reversed the go process bias that typically affects the successful versus failed stop contrast. We recorded scalp electroencephalography in this new version of the task (as well as a standard version of the SST with infrequent stop signal) and found that, even under these conditions, the properties of the frontocentral stop signal P3 ERP remained consistent with the race model. Specifically, in both tasks, the amplitude of the P3 was increased on stop versus go trials. Moreover, the onset of this P3 occurred earlier for successful compared with failed stop trials in both tasks, consistent with the proposal of the race model that an earlier start of the inhibition process will increase stopping success. Therefore, the frontocentral stop signal P3 represents a neural process whose properties are in line with the predictions of the race model of motor inhibition, even when the SST's confounds are controlled.

Many studies have examined the rapid stopping of action as a proxy of human self-control. Several methods have shown that a critical focus for stopping is the right inferior frontal cortex. Moreover, electrocorticography studies have shown beta band power increases in the right inferior frontal cortex and in the BG for successful versus failed stop trials, before the time of stopping elapses, perhaps underpinning a prefrontal–BG network for inhibitory control. Here, we tested whether the same signature might be visible in scalp electroencephalography (EEG)—which would open important avenues for using this signature in studies of the recruitment and timing of prefrontal inhibitory control. We used independent component analysis and time–frequency approaches to analyze EEG from three different cohorts of healthy young volunteers (48 participants in total) performing versions of the standard stop signal task. We identified a spectral power increase in the band 13–20 Hz that occurs after the stop signal, but before the time of stopping elapses, with a right frontal topography in the EEG. This right frontal beta band increase was significantly larger for successful compared with failed stops in two of the three studies. We also tested the hypothesis that unexpected events recruit the same frontal system for stopping. Indeed, we show that the stopping-related right-lateralized frontal beta signature was also active after unexpected events (and we accordingly provide data and scripts for the method). These results validate a right frontal beta signature in the EEG as a temporally precise and functionally significant neural marker of the response inhibition process.

The differences between erroneous actions that are consciously perceived as errors and those that go unnoticed have recently become an issue in the field of performance monitoring. In EEG studies, error awareness has been suggested to influence the error positivity (Pe) of the response-locked event-related brain potential, a positive voltage deflection prominent approximately 300 msec after error commission, whereas the preceding error-related negativity (ERN) seemed to be unaffected by error awareness. Erroneous actions, in general, have been shown to promote several changes in ongoing autonomic nervous system (ANS) activity, yet such investigations have only rarely taken into account the question of subjective error awareness. In the first part of this study, heart rate, pupillometry, and EEG were recorded during an antisaccade task to measure autonomic arousal and activity of the CNS separately for perceived and unperceived errors. Contrary to our expectations, we observed differences in both Pe and ERN with respect to subjective error awareness. This was replicated in a second experiment, using a modified version of the same task. In line with our predictions, only perceived errors provoke the previously established post-error heart rate deceleration. Also, pupil size yields a more prominent dilatory effect after an erroneous saccade, which is also significantly larger for perceived than unperceived errors. On the basis of the ERP and ANS results as well as brain–behavior correlations, we suggest a novel interpretation of the implementation and emergence of error awareness in the brain. In our framework, several systems generate input signals (e.g., ERN, sensory input, proprioception) that influence the emergence of error awareness, which is then accumulated and presumably reflected in later potentials, such as the Pe.