Reconsidering electrophysiological markers of response inhibition in light of trigger failures in the stop-signal task

Abstract

Although advancements in electrophysiological methods to explore response inhibition have been substantial, the methods to describe behavioural differences in response inhibition have remained relatively unchanged. Here we use a model-based neuroscience approach to understand the neural correlates underpinning response inhibition as estimated using a recently developed ex-Gaussian hierarchical Bayesian model of stop-signal task performance. In a large healthy sample (N=156) of community drawn participants, we show the model-based estimates of stop-signal reaction time (SSRT) and a "trigger failure" parameter reflecting lapses of attention to task goals alter previously held interpretations of relationships between inhibition and event-related potential (ERP) component measures.Our results show clear attenuation of SSRT by ≈65ms when substantial levels of trigger failure are accounted for. This attenuation casts doubt on previous interpretations of the P3 as a manifestation of response inhibition. Instead, the N1, which reflects attentional processes, provides a better description of both SSRT and trigger failure than the P3. In particular, the peak N1 latency both correlated and coincided with ex-Gaussian estimated SSRT. Furthermore, participants with higher rates of trigger failure do not show a dissociation between N1 latency and the outcome of a stop trial. Our results show sufficient attentional control to elicit an inhibitory process is just as important, if not more so, than the speed of the process itself and that early ERPs provide a rich account of individual differences in both the speed and reliability of the inhibitory process.

Temporal cascade of frontal, motor and muscle processes underlying human action-stopping

“…within the last 1/3 th of the stopping latency) (Boucher et al, 2007). Indeed, we observed beta bursts in frontal areas ~120 ms after the stop signal followed by rapid cancellation at the muscle within ~40 ms. Third, our results are also compatible with the BEESTS model insofar as they point to a trigger process that has a duration of about 80-120 ms (Bekker et al, 2005;Skippen et al, 2019a). Finally, the interactiverace model and blocked-input model are very similar (Logan et al, 2015), so our results do not disambiguate them.…”

tDCS over the inferior frontal gyri and visual cortices did not improve response inhibition

“…While this corresponds to a large effect, it leaves much unexplained variance that could be driven by factors unique to each measure. Therefore, it seems reasonable to question the extent to which these markers should be used interchangeably as measures of inhibitory timing, a notion which is supported by recent work 57,58 . In sum, though, the correlational pattern suggests that while the different proposed stopping latency markers are not necessarily overlapping in time (Fig.…”

Stimulating stopping? Investigating the effects of tDCS over the inferior frontal gyri and visual cortices

“…While this corresponds to a large effect, it leaves much unexplained variance that could be driven by factors unique to each measure. Therefore, it seems reasonable to question the extent to which these markers should be used interchangeably as measures of inhibitory timing, a notion which is supported by recent work 48,49 . In sum, though, the correlational pattern suggests that while the different proposed stopping latency markers are not necessarily overlapping in time ( Figure 2), they are indeed related to each other as well as to general task processing as quantified by the go reaction times.…”