Neural Oscillation-dependent Electroencephalographic Microstates Reveal Emotional Process-specific Dynamic Neuromarkers of Depression

Depressive affective dysfunction could be manifested by dynamic reorganization processes of functional brain networks under emotional tasks. However, such emotional task-specific reorganizations remain not fully understood in terms of spatiotemporal organization of oscillation dynamics. The insufficiency of approaches for quantifying such dynamic reorganization limits the effective extraction of dynamic neuromarkers of depressive affective dysfunction. To address this gap, this study presents a neural oscillation-dependent microstate approach to quantify the dynamic reorganization process of functional networks at high temporal resolution. The approach was tested by analyzing a 64-channel electroencephalography (EEG) dataset with 110 participants (55 depressed patients and 55 normal controls) collected during emotional tasks with four affective polarities (positive, neutral, negative, and resting state). Our analyses revealed oscillation-dependent microstates that reflected abnormalities in the networks associated with external information processing and interoception in depression. Our analyses further suggest that such abnormalities may be caused by dysfunction in a limited number of brain regions, which then dynamically affects functional brain networks. These findings may reflect increased self-focus and deficits in the perception of external information in depression. In summary, our study further explores source-level evidence related to abnormalities in microstate features of depression based on the generalization of depression microstate research to a multi-band framework. Our study provides a direction for expanding the application of dynamic reorganization analyses of functional networks with high temporal resolution, and provides new support and insights into the neural mechanisms of affective dysfunction in depression.