Evaluation of EEG Microstates and Their Correlation with ECG in Major Depressive Disorder in Resting-State

Major depressive disorder (MDD) is a mental disorder that affects all aspects of social and personal life, as well as causing significant biological and physiological changes in the body. Depression affects the nervous and cardiovascular systems, and these changes can be evaluated using electroencephalogram (EEG) and electrocardiogram (ECG) signals. In this study, the dataset consists of the concurrent EEG and ECG recording from 13 MDD patients and 13 healthy controls (HC), with age and sex-matched, in eyes close (EC) and eyes open (EO) resting states for six minutes. EEG microstates are transient and quasi-stable in the spatial distribution of an EEG and assess brain network activity. We calculated the temporal parameters of four microstates and compared the topographies of microstate clusters using the silhouette method. Finally, R peaks in the ECG were detected, and the numbers of simultaneous EEG microstate labels were counted. The EO state provided better discriminating features than the EC state. Compared to the HC, the duration of microstates B, C, and D was reduced, while microstate A increased in the MDD in the EO state. Based on the silhouette criteria, the fitting of EEG microstates’ topographies is better in the EO state than the EC state for both groups. The analysis of $\mathbf{R}$ peaks revealed a significant increase in the number of peaks in the MDD group compared to the HC group, indicating a correlation between an elevated heart rate and reduced heart rate variability in the studies. The number of concurrent occurrences of R peaks in the ECG with microstate B in the EO state did not show a significant difference between the HC and MDD groups ($\rho=$ 0.132), unlike the other microstates. It is a new approach that could help investigate the relationship between the brain state and the heart.