Performance of Conventional EEG Biomarkers Across Different Clinical Phases of Major Depressive Disorder: A Comprehensive Evaluation

TL;DR

This study evaluates traditional EEG biomarkers across different clinical phases of Major Depressive Disorder, revealing their limited monotonic progression and highlighting the need for improved neurobiological markers for clinical utility.

Contribution

It provides a comprehensive analysis of classic EEG features across MDD phases, uncovering their limitations and emphasizing the importance of individualized approaches.

Findings

Conventional EEG metrics do not show strict monotonic progression across MDD phases.

High inter-individual heterogeneity affects the reliability of group-level EEG biomarkers.

Results suggest a need for new paradigms to identify clinically useful neurobiological markers.

Abstract

While EEG features differentiate Major Depressive Disorder (MDD) from healthy controls (HC), their clinical utility as biomarkers depends on a monotonic trajectory across the disease spectrum, from the acute (AC) phase to the maintenance (MA) phase and finally to the healthy baseline. However, the progression of the MA phase remains poorly understood in traditional marker analysis. Analyzing EEG data from 74 individuals (24 AC, 23 MA, and 27 HC), this study provides a comprehensive evaluation of classic ERP and resting-state indices across AC, MA, and HC groups. Our results demonstrate that almost no conventional metrics strictly satisfy the criterion of monotonic progression, likely due to profound inter-individual heterogeneity. These findings highlight the inherent limitations of group-level feature extraction and provide critical insights for developing future paradigms and algorithms to identify neurobiological markers with genuine clinical utility.