A pilot study investigating a novel non-linear measure of eyes open versus eyes closed EEG synchronization in people with alzheimer’s disease and healthy controls

Daniel J. Blackburn, Yifan Zhao, Matteo De Marco, Simon M. Bell, Fei He, Hua Liang Wei, Sarah Lawrence, Zoe C. Unwin, Michelle Blyth, Jenna Angel, Kathleen Baster, Thomas F.D. Farrow, Iain D. Wilkinson, Stephen A. Billings, Annalena Venneri, Ptolemaios G. Sarrigiannis

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3 Citations (Scopus)
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Abstract

Background: The incidence of Alzheimer disease (AD) is increasing with the ageing population. The development of low cost non-invasive diagnostic aids for AD is a research priority. This pilot study investigated whether an approach based on a novel dynamic quantitative parametric EEG method could detect abnormalities in people with AD. Methods: 20 patients with probable AD, 20 matched healthy controls (HC) and 4 patients with probable fronto temporal dementia (FTD) were included. All had detailed neuropsychology along with structural, resting state fMRI and EEG. EEG data were analyzed using the Error Reduction Ratio-causality (ERR-causality) test that can capture both linear and nonlinear interactions between different EEG recording areas. The 95% confidence intervals of EEG levels of bi-centroparietal synchronization were estimated for eyes open (EO) and eyes closed (EC) states. Results: In the EC state, AD patients and HC had very similar levels of bi-centro parietal synchronization; but in the EO resting state, patients with AD had significantly higher levels of synchronization (AD = 0.44; interquartile range (IQR) 0.41 vs. HC = 0.15; IQR 0.17, p < 0.0001). The EO/EC synchronization ratio, a measure of the dynamic changes between the two states, also showed significant differences between these two groups (AD ratio 0.78 versus HC ratio 0.37 p < 0.0001). EO synchronization was also significantly different between AD and FTD (FTD = 0.075; IQR 0.03, p < 0.0001). However, the EO/EC ratio was not informative in the FTD group due to very low levels of synchronization in both states (EO and EC). Conclusion: In this pilot work, resting state quantitative EEG shows significant differences between healthy controls and patients with AD. This approach has the potential to develop into a useful non-invasive and economical diagnostic aid in AD.

Original languageEnglish
Article number134
JournalBrain Sciences
Volume8
Issue number7
DOIs
Publication statusPublished - 17 Jul 2018
Externally publishedYes

Bibliographical note

This article is an open access article distributed under the terms and conditions of
the Creative Commons Attribution (CC BY) license.

Keywords

  • Alzheimer’s disease
  • Clinical marker
  • Electroencephalography
  • Nonlinear dynamics
  • ROC curve

ASJC Scopus subject areas

  • Neuroscience(all)

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