Abstract
Recurrence quantification analysis is used to detect the P300 event-related potential in a single-trial EEG. It is shown that as a reaction to stimuli, the P300 component is associated with an increase in the complexity of the brain’s electrical activity. It is also shown that recurrence quantification analysis measures are sensitive enough to detect these changes even in single short time series.
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Funding
This work was supported by the Russian Foundation for Basic Research; the National Natural Science Foundation of China, project no. 19-52-55001; and the RF Presidential Grant Council, project no. NSh-2594.2020.2 “For the State Support of Scientific Schools of the Russian Federation.”
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Statement of compliance with standards of research involving humans as subjects. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants involved in the study.
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Translated by A. Deryabina
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Pitsik, N.E. Recurrence Quantification Analysis of P300 Event-Related Potential on Single-Trial EEG. Bull. Russ. Acad. Sci. Phys. 86, 211–215 (2022). https://doi.org/10.3103/S1062873822020241
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DOI: https://doi.org/10.3103/S1062873822020241