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Short-Lived EEG Synchrony Patterns for Alzheimer's Disease Diagnosis

Created on 26 Mar 2026

Authors

Olcay, B. O.

Abstract

Developing a reliable detection of olfactory performance for early Alzheimer's disease (AD) diagnosis remains challenging. Existing methods, such as psychophysical and event-related potential approaches, provide limited consistency in quantifying olfactory function. This study introduces a novel and objective framework that analyzes olfactory-stimulus-evoked EEG synchronizations of the subjects for AD diagnosis. We calculated the time-resolved wavelet coherence between EEG signals and then determined the timings (i.e., latency and duration) that describe when olfactory-stimulus-induced EEG channel interactions begin and end for each channel and frequency band. These timings, as well as the mean synchronization values in these segments, were used as features for diagnosis. Our framework, when cross-correntropy was used as a synchronization measure, exhibited a notable diagnostic accuracy in mild AD detection. The most discriminating feature between mild AD and healthy subjects was found to be the latency of synchronization between Fp1 and Fz in the low theta band, which showed significantly high correlation with clinical test scores. Furthermore, our framework achieved 100% diagnosis accuracy when EEG features and clinical test scores were used together. Our findings show that inter-channel short-lived synchronization timings serve as useful and complementary metrics about subjects' olfactory performance and their neurological conditions.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 26 Mar 2026.

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