Resting-state EEG power and machine-learning classification in adult males with gambling disorder
GD is characterized by subtle but meaningful EEG alterations, particularly increased beta activity linked to gambling severity. Multivariate EEG patterns can distinguish GD from controls, supporting the potential of resting-state EEG as a biomarker for clinical assessment and severity monitoring in behavioral addiction.
Authors
- Selami Varol Ülker (ORCID: https://orcid.org/0000-0002-6385-6418)
- Metin Çınaroğlu (ORCID: https://orcid.org/0000-0001-6342-3949)
- Eda Yılmazer (ORCID: https://orcid.org/0009-0009-3377-5025)
- Sultan Tarlacı
Institutions
- Üsküdar University (TR)
- İstanbul Nişantaşı Üniversitesi (TR)
- Türkisch-Deutsche Universität (TR)
- Beykoz Üniversitesi (TR)
Publication Details
- Journal
- Frontiers in Human Neuroscience
- Published
- 2026-01-13
- DOI
- https://doi.org/10.3389/fnhum.2025.1725528
- Citations
- 1
- Primary Topic
- Gambling Behavior and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 44.11