Decoding acceptance and reappraisal strategies from resting state macro networks

Area of Science:

• Neuroscience
• Cognitive Psychology
• Psychiatry

Background:

• Emotion regulation strategies like acceptance and reappraisal are crucial for mental well-being.
• Previous research utilized task-based fMRI, leaving a gap in understanding resting-state functional brain networks in emotion regulation.
• The neural basis of acceptance, particularly its resting-state network contributions, remains underexplored.

Purpose of the Study:

• To investigate the resting-state functional brain network correlates of acceptance and reappraisal.
• To determine if these emotion regulation strategies share common or distinct neural mechanisms.
• To explore the predictive relationship between specific resting-state networks and individual differences in acceptance and reappraisal abilities.

Main Methods:

• Functional connectivity analysis of resting-state fMRI data from 134 healthy adults.
• Utilized group-Independent Component Analysis (group-ICA) to identify intrinsic brain networks.
• Employed backward regression to predict acceptance and reappraisal scores from network activity.

Main Results:

• Acceptance was associated with decreased activity in affective and executive networks, and increased activity in the sensorimotor network.
• Reappraisal was uniquely predicted by increased activity in the sensorimotor network.
• Findings suggest both distinct (affective/executive for acceptance) and overlapping (sensorimotor for both) neural mechanisms.

Conclusions:

• The sensorimotor network may represent a core common neural mechanism underlying both acceptance and reappraisal.
• Results highlight the complex interplay of cognitive, affective, and sensory systems in adaptive emotion regulation.
• This study expands upon previous findings by elucidating the role of intrinsic brain network organization in emotion regulation strategies.