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Meaningful inhibition: Exploring the role of meaning and modality in response inhibition. | LitMetric

We frequently guide our decisions about when and how to act based on the meanings of perceptual inputs: we might avoid treading on a flower, but not on a leaf. However, most research on response inhibition has used simple perceptual stimuli devoid of meaning. In two Go/No-Go experiments, we examined whether the neural mechanisms supporting response inhibition are influenced by the relevance of meaning to the decision, and by presentation modality (whether concepts were presented as words or images). In an on-line fMRI experiment, we found common regions for response inhibition across perceptual and conceptual decisions. These included the bilateral intraparietal sulcus and the right inferior frontal sulcus, whose neural responses have been linked to diverse cognitive demands in previous studies. In addition, we identified a cluster in ventral lateral occipital cortex that was sensitive to the modality of input, with a stronger response to No-Go than Go trials for meaningful images, compared to words with the same semantic content. In a second experiment, using resting-state fMRI, we explored how individual variation in the intrinsic connectivity of these activated regions related to variation in behavioural performance. Participants who showed stronger connectivity between common inhibition regions and limbic areas in medial temporal and subgenual anterior cingulate cortex were better at inhibition when this was driven by the meaning of the items. In addition, regions with a specific role in picture inhibition were more connected to a cluster in the thalamus/caudate for participants who were better at performing the picture task outside of the scanner. Together these studies indicate that the capacity to appropriately withhold action depends on interactions between common control regions, which are important across multiple types of input and decision, and other brain regions linked to specific inputs (i.e., visual features) or representations (e.g., memory).

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http://dx.doi.org/10.1016/j.neuroimage.2018.06.074DOI Listing

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