Topological data analysis reveals rigid brain-state dynamics during self-viewing in trait rumination.

Area of Science:

• Neuroscience
• Cognitive Psychology
• Psychiatry

Background:

• Rumination, characterized by repetitive, negative self-focused thought, is a maladaptive cognitive style associated with emotional dysregulation and psychiatric conditions.
• Investigating the neural basis of rumination in naturalistic, self-relevant contexts is crucial for understanding its real-world implications.

Purpose of the Study:

• To explore the neural underpinnings of rumination using a novel fMRI paradigm in a naturalistic self-relevant context.
• To examine the relationship between trait rumination and whole-brain dynamics during self-observation and evaluative processing.

Main Methods:

• Developed an fMRI paradigm where participants observed and reflected on videos of their own past group problem-solving sessions.
• Assessed trait rumination using the Rumination-Reflection Questionnaire (RRQ).
• Applied Topological Data Analysis (TDA) with the Mapper algorithm to model individual-level whole-brain dynamics and quantify brain-state similarity.

Main Results:

• Higher trait rumination scores correlated with significantly greater temporal similarity (reduced brain-state variability) during self-relevant conditions (r = 0.46, p = 0.018).
• This effect was specific to self-relevant conditions and not observed during a control condition.
• TDA-Mapper revealed dynamic brain features not captured by traditional static or group-averaged analyses.

Conclusions:

• Trait rumination is associated with rigid large-scale brain dynamics during self-relevant cognition and evaluative processing.
• The findings highlight the utility of combining naturalistic paradigms with topological approaches to identify behaviorally relevant neural signatures.
• This study offers new insights into the neural mechanisms underlying rumination and its link to emotional dysregulation.