A scalp-EEG network-based analysis of Alzheimer's disease patients at rest

Most brain disorders including Alzheimer's disease (AD) are related to alterations in the normal brain network organization and function. Exploring these network alterations using non-invasive and easy to use technique is a topic of great interest. In this paper, we collected EEG resting-state...

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Bibliographic Details
Published in:arXiv.org 2017-06
Main Authors: Kabbara, Aya, Hassan, Mahmoud, Khalil, Mohamad, Wassim El Falou, Eid, Hassan
Format: Article
Language:English
Subjects:
Alzheimer's disease
Band theory
Biomarkers
Brain
Clustering
Electroencephalography
Frequencies
Locking
Patients
Online Access:Get full text
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Summary:Most brain disorders including Alzheimer's disease (AD) are related to alterations in the normal brain network organization and function. Exploring these network alterations using non-invasive and easy to use technique is a topic of great interest. In this paper, we collected EEG resting-state data from AD patients and healthy control subjects. Functional connectivity between scalp EEG signals was quantified using the phase locking value (PLV) for 6 frequency bands. To assess the differences in network properties, graph-theoretical analysis was performed. AD patients showed decrease of mean connectivity, average clustering and global efficiency in the lower alpha band. Positive correlation between the cognitive score and the extracted graph measures was obtained, suggesting that EEG could be a promising technique to derive new biomarkers of AD diagnosis.
ISSN:2331-8422