Altered resting-state sensorimotor network in patients with obsessive-compulsive disorder: An EEG study.

Area of Science:

• Neuroscience
• Clinical Psychology
• Biomarkers

Background:

• Obsessive-compulsive disorder (OCD) is linked to dysfunction in brain circuits, including the sensorimotor network (SMN).
• Previous research using fMRI has shown SMN alterations in OCD, but resting-state EEG (rsEEG) studies are limited.
• This study investigates frequency-specific SMN alterations in OCD using rsEEG.

Purpose of the Study:

• To identify and characterize alterations in the sensorimotor network (SMN) in patients with obsessive-compulsive disorder (OCD) compared to healthy controls (HCs).
• To explore the potential of rsEEG-derived SMN features as diagnostic biomarkers for OCD.

Main Methods:

• Eyes-closed resting-state EEG (rsEEG) data were acquired from 41 OCD patients and 41 HCs.
• Sensorimotor network (SMN) functional connectivity (FC) was analyzed across six frequency bands using the weighted phase-lag index.
• Group differences in FC and strength were assessed, correlated with symptom severity (Y-BOCS), and used for machine learning classification.

Main Results:

• Increased theta band FC between the left S1 and left SMA in OCD patients.
• Increased high alpha band FC between left S1 and right M1/PMC, and increased right PMC local strength in OCD.
• High alpha band FC between left S1 and right M1 positively correlated with Y-BOCS scores; classification accuracy reached 78.05%.

Conclusions:

• Resting-state EEG-derived SMN alterations are evident in individuals with OCD.
• These findings suggest that SMN changes detected by rsEEG may reflect underlying neurophysiological mechanisms of OCD.
• rsEEG-derived SMN features show potential as candidate biomarkers for OCD.