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Electroencephalograms during Mental Arithmetic Task Performance

Author

Listed:
  • Igor Zyma

    (Department of Physiology and Anatomy, Educational and Scientific Center “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv, 01601 Kyiv, Ukraine)

  • Sergii Tukaev

    (Department of Physiology of Brain and Psychophysiology, Educational and Scientific Centre “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv, 01601 Kyiv, Ukraine
    Department of Social Communication, Institute of Journalism, National Taras Shevchenko University of Kyiv, 01601 Kyiv, Ukraine
    Laboratory on Theory and Methodic of Sport Preparation and Reserve Capabilities of Athletes, Scientific Research Institute, National University of Physical Education and Sports of Ukraine, 03150 Kyiv, Ukraine)

  • Ivan Seleznov

    (Department of Electronic Engineering, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 03056 Kyiv, Ukraine
    R&D Engineering, Ciklum, London WC1A 2TH, UK)

  • Ken Kiyono

    (Division of Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka 560-8531, Japan)

  • Anton Popov

    (Department of Electronic Engineering, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 03056 Kyiv, Ukraine
    R&D Engineering, Ciklum, London WC1A 2TH, UK)

  • Mariia Chernykh

    (Department of Biophysics and Medical Informatics, Educational and Scientific Center “Institute of Biology and Medicine”, Taras Shevchenko National University of Kyiv, 01601 Kyiv, Ukraine)

  • Oleksii Shpenkov

    (Department of Physiology and Anatomy, Educational and Scientific Center “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv, 01601 Kyiv, Ukraine)

Abstract

This work has been carried out to support the investigation of the electroencephalogram (EEG) Fourier power spectral, coherence, and detrended fluctuation characteristics during performance of mental tasks. To this aim, the presented dataset contains International 10/20 system EEG recordings from subjects under mental cognitive workload (performing mental serial subtraction) and the corresponding reference background EEGs. Based on the subtraction task performance (number of subtractions and accuracy of the result), the subjects were divided into good counters and bad counters (for whom the mental task required excessive efforts). The data was recorded from 36 healthy volunteers of matched age, all of whom are students of Educational and Scientific Centre “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv (Ukraine); the recordings are available through Physiobank platform. The dataset can be used by the neuroscience research community studying brain dynamics during cognitive workload.

Suggested Citation

  • Igor Zyma & Sergii Tukaev & Ivan Seleznov & Ken Kiyono & Anton Popov & Mariia Chernykh & Oleksii Shpenkov, 2019. "Electroencephalograms during Mental Arithmetic Task Performance," Data, MDPI, vol. 4(1), pages 1-6, January.
    • Handle: RePEc:gam:jdataj:v:4:y:2019:i:1:p:14-:d:198836
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    References listed on IDEAS

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    1. Marc Höll & Holger Kantz, 2015. "The relationship between the detrendend fluctuation analysis and the autocorrelation function of a signal," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(12), pages 1-7, December.
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