Are the neural correlates of stopping and not going identical? Quantitative meta-analysis of two response inhibition...

Neuroimaging studies have utilized two primary tasks to assess motor response inhibition, a major form of inhibitory control: the Go/NoGo (GNG) task and the Stop-Signal Task (SST). It is unclear, however, whether these two tasks engage identical neural systems. This question is critical because assumptions that both tasks are measuring the same cognitive construct have theoretical and practical implications. Many papers have focused on a right hemisphere dominance for response inhibition, with the inferior frontal gyrus (IFG) and the middle frontal gyrus (MFG) receiving the bulk of attention. Others have emphasized the role of the pre-supplementary motor area (pre-SMA). The current study performed separate quantitative meta-analyses using the Activation Likelihood Estimate (ALE) method to uncover the common and distinctive clusters of activity in GNG and SST. Major common clusters of activation were located in the right anterior insula and the pre-SMA. Insular activation was right hemisphere dominant in GNG but more bilaterally distributed in SST. Differences between the tasks were observed in two major cognitive control networks: (1) the fronto-parietal network that mediates adaptive online control, and (2) the cingulo-opercular network implicated in maintaining task set (Dosenbach et al., 2007) and responding to salient stimuli (Seeley et al., 2007). GNG engaged the fronto-parietal control network to a greater extent than SST, with prominent foci located in the right MFG and right inferior parietal lobule. Conversely, SST engaged the cingulo-opercular control network to a greater extent, with more pronounced activations in the left anterior insula and bilateral thalamus. The present results reveal the anterior insula's importance in response inhibition tasks and confirm the role of the pre-SMA. Furthermore, GNG and SST tasks are not completely identical measures of response inhibition, as they engage overlapping but distinct neural circuits.