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Autoregression models of EEG

Results compared with expectations for a multilinear near-equilibrium biophysical process

Abstract

This paper considers the properties of parameters (natural frequencies and damping coefficients) obtained from segment-by-segment autoregression analysis of ECoG of rat. The use of a reference signal as control for parameter estimate errors, and multiple regression analyses indicate that the dependencies among parameters calculated from ECoG in the alert (desynchronised) state are of a form consistent with imposition of time-invariance assumptions (implicit in autoregression) on an inherently non-stationary, multimodal, linear and near-equilibrium “thermal” process.

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This work was supported by the New Zealand Medical Research Council

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Wright, J.J., Kydd, R.R. & Sergejew, A.A. Autoregression models of EEG. Biol. Cybern. 62, 201–210 (1990). https://doi.org/10.1007/BF00198095

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Keywords

  • Regression Analysis
  • Parameter Estimate
  • Estimate Error
  • Multiple Regression Analysis
  • Reference Signal