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Graph-Based EEG Symmetry Features from the Temporal Lobe as Markers of Antidepressant Treatment Response

Akbar DavoodiiD, IOANNIS K. VLACHOSiD, M. Bares, Martin BrunovskýiD, Milan PalušiD

Abstract

Major Depressive Disorder (MDD) is a mental disorder that affects millions globally and has highly individualized responses to antidepressant treatment. Identifying objective early markers that can distinguish responders from non-responders remains a critical challenge in personalized psychiatry. In this study, we investigate the role of brain symmetry in EEG-derived functional connectivity as a potential early marker of treatment response. Using resting-state EEG recordings from 176 patients diagnosed with MDD at baseline (Visit 1) and after one week of treatment (Visit 2), we construct graph-based representations of functional connectivity and define region-wise and electrode-wise temporal-lobe symmetry features. We focus on symmetry change scores (Visit 2 - Visit 1) across typical EEG frequency bands in both weighted and binary forms. Statistical analyses reveal a consistent group-level pattern in the and {beta} bands: responders show negative symmetry change scores, whereas non-responders show relative stability or weakly positive change scores. The contrast is strongest in the {beta}1 band and is more pronounced for binary symmetry metrics, while the band shows the same direction with slightly weaker significance. Physiologically, these opposite trajectories are consistent with a treatment-related shift toward more lateralized temporal-lobe network organization in responders and a more bilateral coupling pattern in nonresponders; however, these neurophysiological interpretations remain hypothesis-generating given the resting-state design and the absence of direct behavioral or task-based validation. To quantify whether temporal symmetry change scores contain reproducible discriminative signal under strict validation, we benchmark the proposed features in a supervised classification pipeline using repeated nested cross-validation. The best-performing configuration achieved a median out-of-sample AUC of 0.690 with a 95% bootstrap confidence interval of [0.611, 0.711], indicating modest but reproducible separability. Overall, temporal-lobe symmetry change features provide interpretable candidate markers of early antidepressant-related neurophysiological change that may complement existing EEG predictors in future multi-marker models, but they are not yet sufficient for standalone clinical decision support and require external validation in independent cohorts.

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02 /Specification & Classification

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