ArticlePsychological medicine2025
Depression links to unstable resting-state brain dynamics: insights from hidden markov models and functional network variability.
Article in Psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Longitudinal brain dynamics and prediction of craving changes in individuals with methamphetamine use disorder.Translational psychiatry · 2026Article
- Nasal and oral breathing modes reconfigure brain network dynamics between stabilizing integration and promoting fragmentation.Scientific reports · 2026Article
- Unveiling state-specific neural dynamics in migraine with and without depressive symptom: a hidden Markov model and interpretable machine learning approach.The journal of headache and pain · 2026Article
- State-specific disruptions of dynamic functional connectivity in young migraine without aura: a hidden Markov model approach.Frontiers in neuroscience · 2026Article
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8 authors.
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Abstract
backgroundDepression is closely associated with abnormalities in brain function. Traditional static functional connectivity analyses offer limited insight into the temporal variability of brain activity. Recent advances in dynamic analyses enable a deeper understanding of how depression relates to temporal fluctuations in brain activity.
methodsThis study utilized a large resting-state functional magnetic resonance imaging dataset (
resultsDepression scores were positively associated with switching rate and negatively associated with maximum fractional occupancy. Furthermore, depression scores were significantly associated with greater temporal variability both within and between networks, with particularly strong effects observed in the default mode network, ventral attention network, and frontoparietal network. Together, these findings suggest that individuals with higher depression scores exhibit more unstable brain dynamics.
conclusionOur findings reveal that individuals with higher depression levels exhibit greater instability in brain state transitions and increased temporal variability in functional connectivity across large-scale networks. This instability in brain dynamics may contribute to difficulties in emotion regulation and cognitive control. By capturing whole-brain temporal patterns, this study offers a novel perspective on the neural basis of depression.
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