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Updated: Jan 12, 2026

Brain Imaging Investigation of the Neural Correlates of Emotion Regulation
Published on: August 26, 2011
Wired to Regulate: Brain Connectivity Predicts Emotion Regulation Capacity and Tendency
C Morawetz1, M Hajrić1, R A Rammensee2
1Department of Psychology, University of Innsbruck, Innsbruck, Austria.
Abstract:
Emotion regulation relies on the flexible coordination of neural networks involved in strategy selection and implementation. While previous studies have focused on task-related brain activity, the role of intrinsic, resting-state connectivity in shaping regulatory tendency in strategy selection and capacity in strategy implementation remains less well understood. Using spectral Dynamic Causal Modeling (spDCM) of resting-state fMRI data, we examined how effective connectivity within four emotion-related brain networks predicts individual differences in the capacity to implement and the tendency to select reappraisal versus distraction for high-intensity emotional stimuli. Forty healthy adults completed two emotion regulation tasks and a 10-min resting-state fMRI scan. We found that distinct and partially overlapping network dynamics predicted both strategy-specific regulation capacity and reappraisal tendency. Notably, the fronto-parietal and parieto-limbic networks were central to both capacity and tendency. In addition, fronto-lateral and limbic networks significantly contributed to the prediction of strategy-specific measures: Reappraisal capacity was associated with broader and more inhibitory connectivity, whereas distraction capacity was related to more localized and mixed excitatory/inhibitory connectivity patterns. Crucially, the connections most predictive of distraction and reappraisal capacity were distinct rather than shared, underscoring the importance of strategy-specific neural adaptations. These findings suggest that intrinsic brain network configurations influence the individual capacity to implement specific strategies and the tendency to select one strategy over the other.
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