{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T08:47:28Z","timestamp":1785833248718,"version":"3.56.0"},"reference-count":19,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Clin. Med.","JCM"],"abstract":"<jats:p>Background\/Objectives: Migraine and tension-type headache (TTH) are common primary headache disorders, but their underlying network-level EEG patterns remain incompletely characterized. We examined whether resting-state functional connectivity measured with complementary estimators, predefined sensor-level regions of interest (ROIs), graph features, and machine-learning models could distinguish migraine, TTH, and healthy controls. Methods: The study included 150 participants (61 migraine, 47 TTH, and 42 controls). Connectivity was calculated in the delta, theta, alpha, beta, and gamma bands using coherence, imaginary coherence, weighted phase-lag index (wPLI), and debiased wPLI. We evaluated global, regional, topographic, and graph-theoretical features, performed ROC-AUC analyses, and tested classification models with nested cross-validation. To limit the multiple-testing burden, false discovery rate correction was applied to a prespecified, hypothesis-driven ROI set. Results: Eight candidate ROI features remained significant after correction. TTH showed the highest gamma temporo-parietal coherence, whereas migraine showed higher gamma temporo-parietal wPLI and debiased wPLI and a higher exploratory migraine probability-like score. Controls had higher delta fronto-temporal and gamma fronto-temporal\/temporo-parietal imaginary coherence. Single-feature ROC-AUC values were moderate, and the nested machine-learning models showed only modest classification performance. Conclusions: The results point to method-dependent, region-specific sensor-level EEG differences across migraine, TTH, and control groups. They are best viewed as candidate neurophysiological signatures rather than clinically ready biomarkers. External validation, fuller clinical covariate assessment, and source-level analyses are needed before diagnostic use can be considered. Future studies should also examine whether these candidate signatures differ according to aura status and episodic or chronic headache subtype.<\/jats:p>","DOI":"10.3390\/jcm15156046","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T08:02:19Z","timestamp":1785830539000},"page":"6046","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["EEG Connectivity Signatures in Migraine and Tension-Type Headache: A Multimethod ROI-Based Functional Connectivity and Machine-Learning Analysis"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6098-9920","authenticated-orcid":false,"given":"Zeynep Selcan","family":"Sanl\u0131","sequence":"first","affiliation":[{"name":"Department of Neurology, Adana City Training and Research Hospital, 01230 Adana, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6640-7917","authenticated-orcid":false,"given":"Ismail","family":"\u00c7al\u0131ku\u015fu","sequence":"additional","affiliation":[{"name":"Biomedical Device Technology Program, Vocational School, Nev\u015fehir Hac\u0131 Bekta\u015f Veli University, 50300 Nevsehir, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8692-8161","authenticated-orcid":false,"given":"Pamir","family":"Bastin","sequence":"additional","affiliation":[{"name":"Department of Neurology, Adana City Training and Research Hospital, 01230 Adana, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8218-2694","authenticated-orcid":false,"given":"Seda Mencekoglu","family":"Bastin","sequence":"additional","affiliation":[{"name":"Department of Neurology, Adana City Training and Research Hospital, 01230 Adana, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0162-4574","authenticated-orcid":false,"given":"Hulya","family":"Binokay","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, \u00c7ukurova University Faculty of Medicine, 01330 Adana, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6799-5100","authenticated-orcid":false,"given":"Vahide Deniz","family":"Yerdelen","sequence":"additional","affiliation":[{"name":"Department of Neurology, Adana City Training and Research Hospital, 01230 Adana, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.1111\/head.14937","article-title":"Global epidemiology and burden of headache disorders in children and adolescents from 1990 to 2021","volume":"65","author":"Lu","year":"2025","journal-title":"Headache J. 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