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Inspection of Short-Time Resting-State Electroencephalogram Functional Networks in Alzheimer's Disease

Escudero, J, Smith, K, Azami, H and Abasolo, Daniel Emilio (2016) Inspection of Short-Time Resting-State Electroencephalogram Functional Networks in Alzheimer's Disease In: EMBC 2016, 2016-08-16 - 2016-08-20, Orlando, USA.

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Abstract

Functional connectivity has proven useful to characterise electroencephalogram (EEG) activity in Alzheimer’s disease (AD). However, most current functional connectivity analyses have been static, disregarding any potential variability of the connectivity with time. In this pilot study, we compute short-time resting state EEG functional connectivity based on the imaginary part of coherency for 12 AD patients and 11 controls. We derive binary unweighted graphs using the cluster-span threshold, an objective binary threshold. For each short-time binary graph, we calculate its local clustering coefficient (Cloc), degree (K), and efficiency (E). The distribution of these graph metrics for each participant is then characterised with four statistical moments: mean, variance, skewness, and kurtosis. The results show significant differences between groups in the mean of K and E, and the kurtosis of Cloc and K. Although not significant when considered alone, the skewness of Cloc is the most frequently selected feature for the discrimination of subject groups. These results suggest that the variability of EEG functional connectivity may convey useful information about AD.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Mechanical Engineering Science
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Escudero, JUNSPECIFIEDUNSPECIFIED
Smith, KUNSPECIFIEDUNSPECIFIED
Azami, HUNSPECIFIEDUNSPECIFIED
Abasolo, Daniel EmilioD.Abasolo@surrey.ac.ukUNSPECIFIED
Date : 18 October 2016
Identification Number : 10.1109/EMBC.2016.7591314
Copyright Disclaimer : © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Contributors :
ContributionNameEmailORCID
UNSPECIFIEDIEEE, UNSPECIFIEDUNSPECIFIED
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 21 Sep 2016 11:06
Last Modified : 11 Jul 2017 09:05
URI: http://epubs.surrey.ac.uk/id/eprint/812265

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