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Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans
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Exploring Alpha Desynchronization in Alzheimer's Disease Using Coherence Analysis

Chun-Wei Lin, Hsiao-Wen Chung, Wen-Chau Wu

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed

    Abstract:

    Electroencephalography (EEG) is a promising tool for early diagnosis of dementia. As the most common form of dementia, Alzheimer's disease (AD) is currently incurable, but patients and those at risk can benefit from timely intervention following accurate diagnosis. Previous studies reported decreased energy in the alpha-band of EEG signals during the transition from the eyes-closed condition to the eyes-open condition, and considered energy as a surrogate index of synchronization (or functional connectivity). In this study, we explored alpha desynchronization by using coherence which is a mathematical index of connectivity. Our results showed that the AD group had lower alpha-band energy and coherence, and diminished alpha desynchronization as compared with the normal control group. Coherence and energy have different implications in synchronization/connectivity (long-range vs. local), and when combined, may advance the understanding of AD pathology-related functional connectivity changes.Clinical Relevance- This study highlights diminished alpha desynchronization in patients with Alzheimer's disease, which may be used as a biomarker for early diagnosis.

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