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psychology.hse@gmail.com

Andrey Mitrofanov 1, Irina Kichuk 2, Margarita Rusalova 3, Svetlana Chausova 4, Nadezhda Solov'eva 5
  • 1 Federal State Budgetary Scientific Institution Mental Health Research Center, 34 Kashirskoye sh., Moscow, 115230, Russia
  • 2 N.I. Pirogov Russian National Research Medical University, 1 Ostrovityanova, Moscow, 117997, Russia
  • 3 Federal State Budgetary Scientific Institution Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5A Butlerova, Moscow, 117485, Russia
  • 4 N.I. Pirogov Russian National Research Medical University, 1 Ostrovityanova, Moscow, 117997, Russia
  • 5 Scientific Center of Personalized Medicine, 20 Bolshaya Pochtovaya, Moscow, 105082, Russia

The Development of the Automated Discriminant Analysis of the EEG to Distinguish Two Classes

2020. Vol. 17. No. 2. P. 223–249 [issue contents]

The authors propose a method of accelerated discriminant analysis procedures using the Software complex "Brainsys" to distinguish two classes.

The software package allows us to consider up to 10 thousand spectral and other EEG parameters that can potentially act as predictors of a linear discriminant function (LDF). Provisionally, the EEG parameters can be transformed to an approximately normal distribution. Various procedures for selecting EEG parameters to satisfy the Fisher model are proposed, as well as procedures for searching for the most useful parameters – candidates for predictors. Procedures for stepwise inclusion of predictors and procedures for testing all possible combinations of predictors were considered. Special attention was paid to the problem of overfitting. Overestimates obtained from training samples can occur due to deviations from the Fisher model or multiple testing. The solution to the problem of overfitting should be found in the confirmation of assessment of the quality of discrimination in independent samples, at least in one. We also consider the issues of obtaining an estimate of the generalization performance (the ability to correctly predict on independent test samples) of a LDF. The method allows checking many variants of discriminant functions without routine calculations or get quick preliminary estimation results by applying the procedure of stepwise inclusion of predictors. A formula of LDF was obtained, which included EEG spectral parameters for differentiating persons with impulsive behavior from persons prone to self-control.
Citation: Mitrofanov A., Kichuk I., Rusalova M., Chausova S., Solov'eva N. (2020) Metodika bystrogo avtomatizirovannogo diskriminantnogo analiza EEG pri razlichenii v dva klassa [The Development of the Automated Discriminant Analysis of the EEG to Distinguish Two Classes]. Psychology. Journal of Higher School of Economics, vol. 17, no 2, pp. 223-249 (in Russian)
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