• DOI:10.1109/ICASSP.2010.5495664
Corpus ID: 16476449

Quantifying EEG synchrony using copulas

@article{Iyengar2010QuantifyingES,
  title={Quantifying EEG synchrony using copulas},
  author={S. G. Iyengar and J. Dauwels and P. Varshney and A. Cichocki},
  journal={2010 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2010},
  pages={505-508}
}

S. G. Iyengar, J. Dauwels, +1 author A. Cichocki

Published 2010

Computer Science

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

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In this paper, we consider the problem of quantifying synchrony between multiple simultaneously recorded electroencephalographic signals. These signals exhibit nonlinear dependencies and non-Gaussian statistics. A copula based approach is presented to model the joint statistics. We then consider the application of copula derived synchrony measures for early diagnosis of Alzheimer's disease. Results on real data are presented.