A Comparative Study of Synchrony Measures for the Early Detection of Alzheimer's Disease Based on EEG

It has repeatedly been reported in the medical literature that the EEG signals of Alzheimer’s disease (AD) patients are less synchronous than in age-matched control patients. This phenomenon, however, does at present not allow to reliably predict AD at an early stage, so-called mild cognitive impairment (MCI), due to the large variability among patients. In recent years, many novel techniques to quantify EEG synchrony have been developed; some of them are believed to be more sensitive to abnormalities in EEG synchrony than traditional measures such as the cross-correlation coefficient. In this paper, a wide variety of synchrony measures is investigated in the context of AD detection, including the cross-correlation coefficient, the mean-square and phase coherence function, Granger causality, the recently proposed correntropy coefficient and two novel extensions, phase synchrony indices derived from the Hilbert transform and time-frequency maps, informationtheoretic divergence measure...

• Type: Conference
• Year: 2007
• Where: ICONIP
• Authors: Justin Dauwels, François B. Vialatte, Andrzej Cichocki
• Keywords: EEG Synchrony, ICONIP 2007, Information Technology, Synchrony, Synchrony Measures