Electrophysiological signatures of developmental dyslexia: towards EEG-based biomarker identification and neurogenetic correlates
| dc.authorid | 0009-0007-8239-8604 | |
| dc.authorid | 0009-0001-4214-8738 | |
| dc.contributor.author | Eroğlu, Günet | en_US |
| dc.contributor.author | Harb, Mhd Raja Abou | en_US |
| dc.date.accessioned | 2025-10-08T07:30:56Z | |
| dc.date.available | 2025-10-08T07:30:56Z | |
| dc.date.issued | 2025-06-30 | |
| dc.department | Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans Programı | en_US |
| dc.department | Işık University, School of Graduate Studies, Master’s Program in Computer Engineering | en_US |
| dc.description.abstract | Dyslexia is a neurodevelopmental disorder characterized by altered hemispheric specialization and disrupted phonological processing. In this study, we applied Principal Component Analysis (PCA) to high-dimensional electroencephalographic (EEG) recordings from 200 children (100 dyslexic, 100 controls) to extract latent neurophysiological features associated with reading impairment. Our findings revealed significant right-hemisphere dominance in dyslexic individuals, particularly in the P8 electrode within the alpha band, consistent with compensatory neural strategies. Despite the absence of clinical comorbidities or medication use, distinct clustering emerged, supporting the utility of PCA for early screening. Future directions include correlating EEG-derived features with known dyslexia-related gene expression profiles (e.g., DCDC2, KIAA0319), neurotransmitter imbalances, and neuroinflammatory markers. These integrative analyses may establish EEG signals as reliable, non-invasive biomarkers for molecular-level screening in developmental learning disorders. | en_US |
| dc.description.version | Preprint's Version | en_US |
| dc.identifier.citation | Eroğlu, G. & Harb, M. R. A. (2025). Electrophysiological signatures of developmental dyslexia: towards EEG-based biomarker identification and neurogenetic correlates. Preprints, 1-11. doi:https://doi.org/10.20944/preprints202506.2457.v1 | en_US |
| dc.identifier.endpage | 11 | |
| dc.identifier.startpage | 1 | |
| dc.identifier.uri | https://hdl.handle.net/11729/6754 | |
| dc.identifier.uri | https://doi.org/10.20944/preprints202506.2457.v1 | |
| dc.identifier.wos | PPRN:156315381 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | en_US |
| dc.indekslendigikaynak | Preprint Citation Index | en_US |
| dc.institutionauthor | Harb, Mhd Raja Abou | en_US |
| dc.institutionauthorid | 0009-0001-4214-8738 | |
| dc.language.iso | en | en_US |
| dc.publisher | MDPI | en_US |
| dc.relation.ispartof | Preprints | en_US |
| dc.relation.publicationcategory | Ön Baskı – Uluslararası – Öğrenci | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Principal component analysis | en_US |
| dc.subject | Electroencephalogram | en_US |
| dc.subject | Dyslexia | en_US |
| dc.title | Electrophysiological signatures of developmental dyslexia: towards EEG-based biomarker identification and neurogenetic correlates | en_US |
| dc.type | Preprint | en_US |
| dspace.entity.type | Publication | en_US |
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