Journal of affective disorders · 2026
Large-scale brain network alteration among OCD patients with suicidal thoughts and behavior: A microstate analysis of the electroencephalogram.
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Zhang Xinyue, Zhu Rongrong, Haider Arsalan, Guo Qihui, Wang Dongmei, Zhang Xiang-Yang
Аннотация
BACKGROUND: The prevalence of suicidality in obsessive-compulsive disorder (OCD) is understudied. Moreover, identifying neurobiological markers of suicidal thoughts and behavior (STBs) is crucial. Electroencephalogram (EEG) microstates, which reflect transient localized brain activity, offer a promising approach to link suicidality in OCD patients with large-scale brain networks, though studies in this area remain limited.
METHODS: Resting-state 64-channel EEG was recorded from a final sample of 99 participants, including 30 OCD patients with STBs (STB), 34 OCD patients without STBs (non-STB), and 35 healthy controls (HCs). Clinical assessments included the Yale-Brown Obsessive-Compulsive Scale, Beck Depression Inventory, and STB-related questions. Microstate parameters were compared across groups, and machine learning (ML) was employed to identify STB-specific features.
RESULTS: Both OCD groups shared abnormalities in certain transition probabilities and temporal parameters compared to HCs. The STB group showed a significantly shorter duration of microstate B compared to the non-STB group. In contrast, the STB group had a significant increase in the occurrence of microstate C and specific transition probabilities relative to HCs. ML classifier achieved balanced accuracies of 96.90% (STB vs. HCs), 97.10% (non-STB vs. HCs), and 65.88% (STB vs. non-STB).
CONCLUSION: These findings indicate that OCD patients with STBs exhibit a distinct pattern in microstate dynamics compared to those without STBs, suggesting that microstate dynamics may serve as useful neurobiological markers for identifying STB risk in OCD patients.
METHODS: Resting-state 64-channel EEG was recorded from a final sample of 99 participants, including 30 OCD patients with STBs (STB), 34 OCD patients without STBs (non-STB), and 35 healthy controls (HCs). Clinical assessments included the Yale-Brown Obsessive-Compulsive Scale, Beck Depression Inventory, and STB-related questions. Microstate parameters were compared across groups, and machine learning (ML) was employed to identify STB-specific features.
RESULTS: Both OCD groups shared abnormalities in certain transition probabilities and temporal parameters compared to HCs. The STB group showed a significantly shorter duration of microstate B compared to the non-STB group. In contrast, the STB group had a significant increase in the occurrence of microstate C and specific transition probabilities relative to HCs. ML classifier achieved balanced accuracies of 96.90% (STB vs. HCs), 97.10% (non-STB vs. HCs), and 65.88% (STB vs. non-STB).
CONCLUSION: These findings indicate that OCD patients with STBs exhibit a distinct pattern in microstate dynamics compared to those without STBs, suggesting that microstate dynamics may serve as useful neurobiological markers for identifying STB risk in OCD patients.