Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/101138
Title: Slowing and loss of complexity in Alzheimer's EEG : two sides of the same coin?
Authors: Srinivasan, K.
Dauwels, Justin
Reddy, M. Ramasubba
Musha, Toshimitsu
Vialatte, François-Benoît
Latchoumane, Charles
Jeong, Jaeseung
Cichocki, Andrzej
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2011
Source: Dauwels, J., Srinivasan, K., Reddy, M. R., Musha, T., Vialatte, F.-B., Latchoumane, C. et al. (2011). Slowing and loss of complexity in Alzheimer's EEG : two sides of the same coin? International journal of Alzheimer's disease, 2011, 539621-.
Series/Report no.: International journal of alzheimer's disease
Abstract: Medical studies have shown that EEG of Alzheimer's disease (AD) patients is “slower” (i.e., contains more low-frequency power) and is less complex compared to age-matched healthy subjects. The relation between those two phenomena has not yet been studied, and they are often silently assumed to be independent. In this paper, it is shown that both phenomena are strongly related. Strong correlation between slowing and loss of complexity is observed in two independent EEG datasets: (1) EEG of predementia patients (a.k.a. Mild Cognitive Impairment; MCI) and control subjects; (2) EEG of mild AD patients and control subjects. The two data sets are from different patients, different hospitals and obtained through different recording systems. The paper also investigates the potential of EEG slowing and loss of EEG complexity as indicators of AD onset. In particular, relative power and complexity measures are used as features to classify the MCI and MiAD patients versus age-matched control subjects. When combined with two synchrony measures (Granger causality and stochastic event synchrony), classification rates of 83% (MCI) and 98% (MiAD) are obtained. By including the compression ratios as features, slightly better classification rates are obtained than with relative power and synchrony measures alone.
URI: https://hdl.handle.net/10356/101138
http://hdl.handle.net/10220/18352
ISSN: 2090-0252
DOI: 10.4061/2011/539621
Schools: School of Electrical and Electronic Engineering 
Rights: © 2011 The Author(s). This paper was published in International Journal of Alzheimer's Disease and is made available as an electronic reprint (preprint) with permission of The Author(s). The paper can be found at the following official DOI: http://dx.doi.org/10.4061/2011/539621.  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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