A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG

By Justin H. G. Dauwels, François-Benoît Vialatte, Toshimitsu Musha, Andrzej S. Cichocki. NeuroImage, 2010

424 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/77bbece92df3a11501550de43442f4a1d574f0f1

How researchers see this paper

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In Cognitive Neuroscience

1. Andrzej S. Cichocki
2. Justin H. G. Dauwels
3. François-Benoît Vialatte
4. Vangelis Sakkalis

Citations in the corpus

• Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG (2011, background): “More recently GC, phase synchrony and nonlinear generalized synchronization based measures have also been tested in AD [65].”
• Network modelling methods for FMRI (2011, neutral): “Generalised (or nonlinear) synchronisation “evaluates synchrony by analysing the interdependence between the signals in a state space reconstructed domain” (Dauwels et al., 2010).”
• Diagnosis of Alzheimer's disease from EEG signals: where are we standing? (2010, background): “In a recent study, it was shown that many classical and recently proposed similarity measures, although developed from different perspectives, lead to similar numerical values [96] [97] (at least for one particular EEG data set).”