MURAL - Maynooth University Research Archive Library

    Nonlinear time series analysis of human alpha rhythm

    Nolte, G and Sander, T and Lueschow, A and Pearlmutter, Barak A. (2002) Nonlinear time series analysis of human alpha rhythm. In: Proceedings of the 13th International Conference on Biomagnetism, August 10-14, 2002, Jena, Germany.

    [img] Download (92kB)
    Official URL:

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    Nonlinearity is often deduced by showing that a dataset signi£cantly deviates from its phase randomized versions, i.e. surrogate data. For real data, however, non-stationarities like artifacts and onsets and offsets of rhythmic activity will cause false positives. We propose a new test which detects dynamical nonlinearity by measuring time-asymmetry, using surrogate data merely to estimate the standard deviation of the process. The method is applied to multi-channel MEG measurements of ongoing alpha-band activity modulated by a simple visual memory task involving motor activity. The signal to noise ratio was enhanced using ICA, and the analysis was performed on a single separated source. We found that, if the peak at 10 Hz is accompanied by a substantial higher harmonic, time asymmetry can be detected signifcantly in virtually any epoch of 3 second duration. Finally, we applied our recently proposed method to estimate correlation dimension for noisy data. We found very satisfactory scaling plots with dimension around 1.5. As a byproduct, we showed that the nondeterministic fraction can be explained almost completely by external noise.

    Item Type: Conference or Workshop Item (Paper)
    Keywords: Non-linearity; Detecting nonlinearity; Noise.
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 1420
    Depositing User: Barak Pearlmutter
    Date Deposited: 02 Jun 2009 15:13
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads