Dynamic Entropic Mapping of Alzheimer's Neuropathology: Eyes-Open and Eyes-Closed EEG Biomarkers through Wavelet Entropy Analysis.

Background

Alzheimer's Disease (AD) is characterized by amyloid-β plaques and tau tangles, while current diagnostic tools are often invasive and costly. Electroencephalography (EEG) offers a non-invasive alternative, with alpha rhythm abnormalities as key features. Impaired alpha reactivity during the transition from Eyes-Closed (EC) to Eyes-Open (EO) reflects early thalamocortical dysfunction.

Objective

This study employs EO/EC wavelet entropy analysis to assess neurodynamic features across frequency bands, aiming to explore entropy-based EEG markers for early AD detection.

Methods

This cross-sectional study enrolled 60 participants (30 AD and 30 controls). EEG was recorded during 60-second EC and Eyes-Open (EO) states using a 20-channel system. Continuous Wavelet Transform (CWT) and multiscale entropy were used to assess complexity differences across bands and regions between groups.

Results

AD patients showed reduced alpha entropy differences between EC and EO states. Multiscale entropy difference (ΔEN α ) analysis revealed weaker modulation in β-α and θ-δ bands compared with HC. Occipital ΔEN α correlated significantly with MMSE, with the strongest association in the alpha band (r = 0.9000, P < 0.001).

Discussion

This study applies dual-state wavelet entropy analysis to reveal impaired neural reactivity in AD during eyes-open and eyes-closed transitions. The ΔEN α metric distinguishes AD from controls and correlates with cognitive decline, reflecting reduced neural flexibility and disrupted frequency-specific network dynamics.

Conclusion

This study shows that dual-state wavelet entropy analysis, especially ΔEN α, is a noninvasive tool for detecting neurodynamic abnormalities in AD. It reflects loss of state-dependent responsiveness and neural complexity, with potential for early screening and objective evaluation of treatment.