Multiscale Dispersion Entropy of Resting‐State EEG in Older Adults with Alzheimer's Dementia, Mild Cognitive Impairment, or remitted Major Depressive Disorder
Hamed Azami, Mary Pat McAndrews, Mostafa Rostaghi, Reza Zomorrodi, Heather Brooks, Daniel M. Blumberger, Corinne E. Fischer, Alastair Flint, Nathan Herrmann, Sanjeev Kumar, Damien Gallagher, Linda Mah, Benoit H. Mulsant, Bruce G. Pollock, Tarek K Rajji

TL;DR
This study uses brain wave analysis to show that people with Alzheimer's or memory issues have less complex brain activity at short time scales compared to healthy individuals.
Contribution
The study introduces multiscale dispersion entropy to distinguish Alzheimer's dementia, mild cognitive impairment, and healthy controls based on resting-state EEG.
Findings
Alzheimer's patients showed reduced short-scale MDE compared to MCI and healthy controls.
Cognitive performance was linked to MDE at short time scales but not long time scales.
MDD remission did not affect MDE, suggesting cognitive complexity changes are tied to active depression.
Abstract
Multiscale dispersion entropy (MDE) is a nonlinear approach for assessing the complexity of brain activity using electroencephalograms (EEGs). MDE captures EEG dynamics across biologically relevant time scales, with short‐scales reflecting high‐frequency oscillations and local neuronal activity, and long‐scales representing low‐frequency oscillations and large‐scale network processes. Previous studies suggest that patients with Alzheimer's dementia (AD) have decreased complexity at short time scales compared to those with mild cognitive impairment (MCI) or healthy controls (HCs), and individuals with MCI show reduced complexity compared to HCs. There is also preliminary evidence suggesting that adult patients with acute depression –a high‐risk condition for AD– have decreased complexity at a short time scale. Thus, we conducted a study in older participants with AD, MCI, HC, remitted…
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Taxonomy
TopicsFunctional Brain Connectivity Studies · EEG and Brain-Computer Interfaces · Heart Rate Variability and Autonomic Control
