Distinct neurodynamics of functional brain networks in Alzheimer's disease and frontotemporal dementia as revealed by EEG
Sungwoo Ahn, Evie A. Malaia, Leonid L Rubchinsky

TL;DR
This study characterizes distinct neural dynamic patterns in Alzheimer's disease and frontotemporal dementia using EEG, revealing opposite alterations in brain coordination and connectivity that may underpin their specific neurological deficits.
Contribution
It provides a comprehensive analysis of neural dynamics differences between AD and FTD using advanced EEG measures and machine learning, highlighting their opposite neurodynamical alterations.
Findings
AD shows less coordinated, more random neural activity.
FTD exhibits more synchronized neural activity.
Distinct EEG patterns differentiate AD and FTD from controls.
Abstract
Objective While Alzheimer's disease (AD) and frontotemporal dementia (FTD) show some common memory deficits, these two disorders show partially overlapping complex spatiotemporal patterns of neural dynamics. The objective of this study is to characterize these patterns to better understand the general principles of neurodynamics in these conditions. Methods A comprehensive array of methods to study brain rhythms and functional brain networks are used in the study, from spectral power measures to Lyapunov exponent, phase synchronization, temporal synchrony patterns, and measures of the functional brain connectivity. Furthermore, machine learning techniques for classification are used to augment the methodology. Results Multiple measures (spectral, synchrony, functional network organization) indicate an array of differences between neurodynamics between AD and FTD, and control…
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