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.