{"doi":"10.64898/2026.01.26.701781","title":"Graph-Based EEG Symmetry Features from the Temporal Lobe as Markers of Antidepressant Treatment Response","abstract":"<jats:p>\n                  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\n                  <jats:italic>change scores</jats:italic>\n                  (Visit 2 − Visit 1) across typical EEG frequency bands in both weighted and binary forms.\n                </jats:p>\n                <jats:p>\n                  Statistical analyses reveal a consistent group-level pattern in the\n                  <jats:italic>α</jats:italic>\n                  and\n                  <jats:italic>β</jats:italic>\n                  bands: responders show negative symmetry change scores, whereas non-responders show relative stability or weakly positive change scores. The contrast is strongest in the\n                  <jats:italic>β</jats:italic>\n                  <jats:sub>1</jats:sub>\n                  band and is more pronounced for binary symmetry metrics, while the\n                  <jats:italic>α</jats:italic>\n                  band shows the same direction with slightly weaker significance. Physiologically, these opposite trajectories are\n                  <jats:italic>consistent with</jats:italic>\n                  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.\n                </jats:p>\n                <jats:p>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.</jats:p>\n                <jats:p>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.</jats:p>","journal":null,"year":null,"id":687688,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1139386,"name":"Ioannis Vlachos","orcid":null,"position":1,"is_corresponding":false},{"id":1796555,"name":"Martin Bareš","orcid":null,"position":2,"is_corresponding":false},{"id":1036303,"name":"Martin Brunovský","orcid":"0000-0002-2483-0848","position":3,"is_corresponding":false},{"id":1796556,"name":"Milan Paluš","orcid":"0000-0001-8474-1436","position":4,"is_corresponding":false},{"id":1796554,"name":"Akbar Davoodi","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Graph-Based EEG Symmetry Features from the Temporal Lobe as Markers of Antidepressant Treatment Response","abstract":"<jats:p>\n                  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\n                  <jats:italic>change scores</jats:italic>\n                  (Visit 2 − Visit 1) across typical EEG frequency bands in both weighted and binary forms.\n                </jats:p>\n                <jats:p>\n                  Statistical analyses reveal a consistent group-level pattern in the\n                  <jats:italic>α</jats:italic>\n                  and\n                  <jats:italic>β</jats:italic>\n                  bands: responders show negative symmetry change scores, whereas non-responders show relative stability or weakly positive change scores. The contrast is strongest in the\n                  <jats:italic>β</jats:italic>\n                  <jats:sub>1</jats:sub>\n                  band and is more pronounced for binary symmetry metrics, while the\n                  <jats:italic>α</jats:italic>\n                  band shows the same direction with slightly weaker significance. Physiologically, these opposite trajectories are\n                  <jats:italic>consistent with</jats:italic>\n                  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.\n                </jats:p>\n                <jats:p>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.</jats:p>\n                <jats:p>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.</jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26207759","pmcid":null,"openalex_id":"https://openalex.org/W7125795523","authors":[],"funders":[{"funder_name":"","grant_id":"GF21-14727K","title":null},{"funder_name":"Czech Academy of Sciences","grant_id":"Praemium Academiae","title":null},{"funder_name":"European Regional Development","grant_id":"CZ.02.01.01/00/22_008/0004643","title":null}],"total_grants":3,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.64898/2026.01.26.701781","host_type":"repository"},{"url":"https://doi.org/10.64898/2026.01.26.701781","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.64898/2026.01.26.701781","host_type":"publisher"}],"fields_of_study":["Functional Brain Connectivity Studies","EEG and Brain-Computer Interfaces","Mental Health Research Topics"],"mesh_terms":[],"keywords":["Symmetry (geometry)","Electroencephalography","Temporal lobe","Pattern recognition (psychology)","Discriminative model","Binary number","Major depressive disorder","Neurophysiology","Generalization"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Reduced inequalities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-18T22:29:32.711523Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}