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Classification of brain activities during language and music perception

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Abstract

Analysis of brain activities in language perception for individuals with different musical backgrounds can be based upon the study of multichannel electroencephalograhy (EEG) signals acquired in different external conditions. The present paper is devoted to the study of the relationship of mental processes and the perception of external stimuli related to the previous musical education. The experimental set under study included 38 individuals who were observed during perception of music and during listening to foreign languages in four stages, each of which was 5 min long. The proposed methodology is based on the application of digital signal processing methods, signal filtering, statistical methods for signal segment selection and active electrode detection. Neural networks and support vector machine (SVM) models are then used to classify the selected groups of linguists to groups with and without a previous musical education. Our results include mean classification accuracies of 82.9% and 82.4% (with the mean cross-validation errors of 0.21 and 0.22, respectively) for perception of language or music and features based upon EEG power in the beta and gamma EEG frequency bands using neural network and SVM classification models.

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Acknowledgements

The authors would like to express their thanks to all of the individuals who were involved in this research. The whole study was partially supported by the grant projects of the Ministry of Health of the Czech Republic (FN HK 00179906) and of the Charles University in Prague, Czech Republic (PROGRES Q40).

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Authors and Affiliations

  1. Department of German Language and Literature, Faculty of Education, University of Hradec Králové, 500 03, Hradec Králové, Czech Republic

    Petra Besedová & Jana Ondráková

  2. Department of Neurology, Faculty of Medicine in Hradec Králové, Charles University in Prague, 500 05, Hradec Králové, Czech Republic

    Oldřich Vyšata, Radka Mazurová & Martin Vališ

  3. Department of Computing and Control Engineering, University of Chemistry and Technology in Prague, 166 28, Prague 6, Czech Republic

    Jakub Kopal & Aleš Procházka

  4. Czech Technical University in Prague, Czech Institute of Informatics, Robotics and Cybernetics, 166 36, Prague 6, Czech Republic

    Jakub Kopal & Aleš Procházka

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  1. Petra Besedová
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Correspondence to Aleš Procházka.

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Besedová, P., Vyšata, O., Mazurová, R. et al. Classification of brain activities during language and music perception. SIViP 13, 1559–1567 (2019). https://doi.org/10.1007/s11760-019-01505-5

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