  Acceptance and Reappraisal are considered adaptive emotion regulation
strategies. While previous studies have explored the neural underpinnings of
these strategies using task based fMRI and sMRI, a gap exists in the literature
concerning resting-state functional brain networks contributions to these
abilities, especially for what concerns Acceptance. Another intriguing question
is whether these strategies rely on similar or different neural mechanisms.
Building on the well-known improved emotion regulation and increased cognitive
flexibility of individuals who rely on acceptance, we expected to find
decreased activity inside the Affective network and increased activity inside
the Executive and Sensorimotor networks to be predicted of acceptance. We also
expect that these networks may be associated at least in part with Reappraisal,
indicating a common mechanism behind different strategies. To test these
hypotheses, we conducted a functional connectivity analysis of resting-state
data from 134 individuals (95 females). To assess acceptance and reappraisal
abilities, we used the Cognitive Emotion Regulation Questionnaire (CERQ) and a
group-ICA unsupervised machine learning approach to identify resting state
networks. Subsequently, we conducted backward regression to predict acceptance
and reappraisal abilities. As expected, results indicated that acceptance was
predicted by decreased Affective, and increased Executive, and Sensorimotor
networks, while reappraisal was predicted by an increase in the Sensorimotor
network. Notably, these findings suggest both distinct and overlapping brain
contributions to acceptance and reappraisal, with the Sensorimotor network
potentially serving as a core common mechanism. These results not only align
with previous findings but also expand upon them, demonstrating the complex
interplay of cognitive, affective, and sensory abilities in emotion regulation.
