Biological Cybernetics

, Volume 105, Issue 3–4, pp 183–195

Application of modern tests for stationarity to single-trial MEG data

Transferring powerful statistical tools from econometrics to neuroscience
  • Lech Kipiński
  • Reinhard König
  • Cezary Sielużycki
  • Wojciech Kordecki
Open Access
Original Paper

DOI: 10.1007/s00422-011-0456-4

Cite this article as:
Kipiński, L., König, R., Sielużycki, C. et al. Biol Cybern (2011) 105: 183. doi:10.1007/s00422-011-0456-4

Abstract

Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro–Wilk test or Kolmogorov–Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity—the Kwiatkowski–Phillips–Schmidt–Schin (KPSS) test for trend or mean stationarity, the Phillips–Perron (PP) test for the presence of a unit root and the White test for homoscedasticity—on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.

Keywords

Magnetoencephalography (MEG) Nonstationarity Heteroscedasticity KPSS test PP test White test 

Copyright information

© The Author(s) 2011

Authors and Affiliations

  • Lech Kipiński
    • 1
    • 2
    • 3
  • Reinhard König
    • 4
  • Cezary Sielużycki
    • 4
  • Wojciech Kordecki
    • 3
    • 5
  1. 1.Department of PathophysiologyWrocław Medical UniversityWrocławPoland
  2. 2.Department of NeurologyT. Marciniak Memory Lower Silesia Specialist Hospital—Medical Emergency CentreWrocławPoland
  3. 3.Institute of Biomedical Engineering and Instrumentation, Wrocław University of TechnologyWrocławPoland
  4. 4.Special Lab Non-invasive Brain Imaging, Leibniz Institute for NeurobiologyMagdeburgGermany
  5. 5.Department of Economics and AccountancyUniversity of Business in WrocławWrocławPoland

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