ArticleHuman brain mapping2024
Resting-state effective connectivity is systematically linked to reappraisal success of high- and low-intensity negative emotions.
Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Review
- Remodeling of the ventral attention network-default mode network as potential neural correlates of anxiety in lumbar disc herniation patients treated with lever positioning manipulation: a resting-state fMRI study.BMC complementary medicine and therapies · 2026Article
- A dual-fMRI investigation of interpersonal emotion regulation: Predicting strategy selection and implementation success from effective brain connectivity.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Article
- Wired to Regulate: Brain Connectivity Predicts Emotion Regulation Capacity and Tendency.Human brain mapping · 2025Article
- Segregation of three resting-state brain networks predicts reappraisal success across the lifespan.Social cognitive and affective neuroscience · 2025Article
- Different association patterns of emotion regulation and heart rate variability in older and younger adults.Brain communications · 2025Article
- Resting-state effective connectivity is systematically linked to reappraisal success of high- and low-intensity negative emotions.Human brain mapping · 2024Article
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
Abstract
Emotion regulation is a process by which individuals modulate their emotional responses to cope with different environmental demands, for example, by reappraising the emotional situation. Here, we tested whether effective connectivity of a reappraisal-related neural network at rest is predictive of successfully regulating high- and low-intensity negative emotions in an emotion-regulation task. Task-based and resting-state functional magnetic resonance imaging (rs-fMRI) data of 28 participants were collected using ultra-high magnetic field strength at 7 Tesla during three scanning sessions. We used spectral dynamic causal modeling (spDCM) on the rs-fMRI data within brain regions modulated by emotion intensity. We found common connectivity patterns for both high- and low-intensity stimuli. Distinctive effective connectivity patterns in relation to low-intensity stimuli were found from frontal regions connecting to temporal regions. Reappraisal success for high-intensity stimuli was predicted by additional connections within the vlPFC and from temporal to frontal regions. Connectivity patterns at rest predicting reappraisal success were generally more pronounced for low-intensity stimuli, suggesting a greater role of stereotyped patterns, potentially reflecting preparedness, when reappraisal was relatively easy to implement. The opposite was true for high-intensity stimuli, which might require a more flexible recruitment of resources beyond what is reflected in resting state connectivity patterns. Resting-state effective connectivity emerged as a robust predictor for successful reappraisal, revealing both shared and distinct network dynamics for high- and low-intensity stimuli. These patterns signify specific preparatory states associated with heightened vigilance, attention, self-awareness, and goal-directed cognitive processing, particularly during reappraisal for mitigating the emotional impact of external stimuli. Our findings hold potential implications for understanding psychopathological alterations in brain connectivity related to affective disorders.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.