Time: Thursday, April 23, 2026, at 12:30 p.m.
Location: Room 1100, 11th Floor, Lü Dalong Building, Tsinghua University
Presentation Topic： Large-scale brain network alteration among OCD patients with suicidal thoughts and behavior: a microstate analysis of the electroencephalogram
Speaker: Xinyue Zhang
Abstract：
The prevalence of suicidality in obsessive-compulsive disorder (OCD) patients is underestimated. 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. Resting-state 64-channel EEG was analyzed 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. 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). 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.
