Related neural networks underlie suppression of emotion, memory, motor processes as identified by data-driven analysis.

Background: Goal-directed behavior benefits from self-regulation of cognitive and affective processes, such as emotional reactivity, memory retrieval, and prepotent motor response. Dysfunction in self-regulation is a common characteristic of many psychiatric disorders, such as PTSD and ADHD. This study sought to determine whether common intrinsic connectivity networks (ICNs; e.g. default mode network) are involved in the regulation of emotion, motor, and memory processes, and if a data-driven approach using independent component analysis (ICA) would successfully identify such ICNs that contribute to inhibitory regulation.

Methods: Eighteen participants underwent neuroimaging while completing an emotion regulation (ER) task, a memory suppression (Think/No-Think; TNT) task, and a motor inhibition (Stop Signal; SS) task. ICA (CONN; MATLAB) was conducted on the neuroimaging data from each task and corresponding components were selected across tasks based on interrelated patterns of activation. Subsequently, ICNs were correlated with behavioral performance variables from each task.

Results: ICA indicated a common medial prefrontal network, striatal network, and frontoparietal executive control network, as well as downregulation in task-specific ROIs.

Conclusions: These results illustrate that common ICNs were exhibited across three distinct inhibitory regulation tasks, as successfully identified through a data-driven approach (ICA).