Alzheimer's disease (AD) is a neurodegenerative brain disease affecting cognitive and physical functioning. The currently available pharmacological treatments for AD mainly contain cholinesterase inhibitors (AChE-I) and N-methyl-D-aspartic acid (NMDA) receptor antagonists (i.e., memantine). Because brain signals have complex nonlinear dynamics, there has been an increase in interest in researching complexity changes in the time series of brain signals in individuals with AD. In this study, we explore the electroencephalographic (EEG) complexity for making better observation of pharmacological therapy-based treatment effects on AD patients using the permutation entropy (PE) method. We examined EEG sub-band (delta, theta, alpha, beta, and gamma) complexity in de-novo, monotherapy (AChE-I), dual therapy (AChE-I and memantine) receiving AD participants compared with healthy elderly controls. We showed that each frequency band depicts its own complexity profile, which is regionally altered between groups. These alterations were also found to be associated with global cognitive scores. Overall, our findings indicate that entropy measures could be useful to show medication effects in AD.
Keywords: Alzheimer’s disease; Dementia medications; EEG complexity; EEG frequencies; Permutation entropy.
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