Usefulness of non-linear EEG analysis

S Micheloyannis, N Flitzanis, E Papanikolaou, M Bourkas, D Terzakis, S Arvanitis, C J Stam

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Spectral analysis methods are useful for the evaluation of EEG signals. Nevertheless, they refer only to the frequency domain and ignore any potentially interesting phase information. Analytical methods based upon the theory of nonlinear dynamics provides this and additional information. We used both methods to evaluate the EEG signals of volunteers performing two distinct mental arithmetic tasks. We extracted the power spectrum, the coherence and nonlinear parameters (dimension, the first Lyapunov exponent, the Kolmogorov entropy, the mutual dimension and the dimensions based upon spatial embedding of the original data as well as their surrogates). We found that 1) the spatial embedding dimension differed from that of the surrogates, indicating nonlinearity, 2) there were differences between the two arithmetic tasks, and 3) the spectral and nonlinear methods differ in terms of the information they provide. Our results indicate that nonlinear analysis methods can be useful despite the fact that they are still at an early stage of development.

Original languageEnglish
Pages (from-to)13-9
Number of pages7
JournalActa Neurologica Scandinavica
Volume97
Issue number1
Publication statusPublished - Jan 1998

Cite this

Micheloyannis, S., Flitzanis, N., Papanikolaou, E., Bourkas, M., Terzakis, D., Arvanitis, S., & Stam, C. J. (1998). Usefulness of non-linear EEG analysis. Acta Neurologica Scandinavica, 97(1), 13-9.