Random matrix analysis of human EEG data
Language English Country United States Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Electroencephalography methods MeSH
- Data Interpretation, Statistical * MeSH
- Humans MeSH
- Models, Statistical * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
We use random matrix theory to demonstrate the existence of generic and subject-independent features of the ensemble of correlation matrices extracted from human EEG data. In particular, the spectral density as well as the level spacings was analyzed and shown to be generic and subject independent. We also investigate number variance distributions. In this case we show that when the measured subject is visually stimulated the number variance displays deviations from the random matrix prediction.
References provided by Crossref.org
