Authors
Boris-Stephan Rauchmann, James Hamet, Jesyin Lai, Homeira Kafi, Joe Rexwinkle, Matthias Brendel, Nicolai Franzmeier, Carolin Kurz, Oliver Pogarell, Johannes Levin, Günter Höglinger, Robert Perneczky
Published in
Alzheimer's research & therapy. Jun 12, 2026. Epub Jun 12, 2026.
Abstract
Dementia affects over 50 million individuals globally, predominantly due to Alzheimer's disease (AD). Effective early detection and intervention remain clinical challenges, as there is a lack of unified, portable solutions to assess multiple biomarkers.
We evaluated Evoked Potential Tomography (EPT), an EEG-based method using a novel visual evoked potential protocol. An automated pipeline for EEG preprocessing, ERP extraction, feature selection, optimization, and regression modeling was developed to estimate key AD biomarkers: PET-amyloid standardized uptake value ratio (SUVR), CSF phosphorylated tau (p-tau181), Free and Cued Selective Reminding Test (FCSRT), and Mini-Mental State Examination (MMSE) scores.
Regression models using ERP features from dementia participants demonstrated strong correlations (r = 0.8-0.94, p < 0.01) between predicted and true PET-amyloid SUVR, p-tau181, FCSRT, and MMSE values. In an independent external cohort, PET-amyloid SUVR predictions remained significantly associated with true values (r = 0.60, p < 0.01).
Despite limitations, these preliminary results support EPT's potential as a sensitive and non-invasive method for estimating AD-related biomarkers in a clinically enriched AD cohort. Further validation studies are ongoing.
PMID:
42286647
Bibliographic data and abstract were imported from PubMed on 13 Jun 2026.
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