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Individual Theta/Beta Based Algorithm for Neurofeedback Games to Improve Cognitive Abilities

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Transactions on Computational Science XXVI

Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 9550))

Abstract

NeuroFeedback Training (NFT) can be used to enhance cognitive abilities in healthy adults. In this paper, we propose and implement a neurofeedback system which integrates an individual theta/beta based neurofeedback algorithm in a “Shooting” game. The system includes an algorithm of calculation of an Individual Alpha Peak Frequency (IAPF), Individual Alpha Band Width (IABW) and individual theta/beta ratio. Use of the individual theta/beta ratio makes the neurofeeback training more effective. We study the effectiveness of the proposed neurofeedback system with five subjects taking 6 NFT sessions each. As the neurofeedback protocol based on the power of individual theta/beta ratio training is used, each neurofeedback training session includes an IAPF, IABW and individual theta/beta ratio calculation. Subjects play the “Shooting” game to train cognitive abilities. The feedback on the player’s brain state is given by the color of the shooter’s target. If the target turns from “blue” to “red”, the player is in the “desired” brain state and is able to shoot. IAPF and IABW parameters calculated before and after NFT sessions are used for neurofeedback efficiency analysis. Our hypothesis is that after the neurofeedback training by playing the “Shooting” game, the individual alpha peak frequency increases. The results show that all subjects overall have a higher individual alpha peak frequency values right after the training or the next day.

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Acknowledgments

This research was done for Fraunhofer IDM@NTU, which is funded by the National Research Foundation (NRF) and managed through the multi-agency Interactive & Digital Media Programme Office (IDMPO) hosted by the Media Development Authority of Singapore (MDA). The “Shooting” game is original and designed by NTU final year student Qiuyu Xiang using UDK game engine.

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Authors and Affiliations

  1. Fraunhofer IDM@NTU, Nanyang Technological University, Singapore, Singapore

    Yisi Liu, Xiyuan Hou & Olga Sourina

  2. Scientific Research Institute of Physiology and Basic Medicine, Russian Academy of Medical Sciences, Moscow, Russia

    Olga Bazanova

Authors
  1. Yisi Liu
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  2. Xiyuan Hou
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  3. Olga Sourina
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  4. Olga Bazanova
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Corresponding author

Correspondence to Yisi Liu .

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Editors and Affiliations

  1. University of Calgary, Calgary, Alberta, Canada

    Marina L. Gavrilova

  2. Sardina Systems OÜ, Tallinn, Estonia

    C.J. Kenneth Tan

  3. University of Cantabria, Santander, Spain

    Andrés Iglesias

  4. Toho University, Tokyo, Japan

    Mikio Shinya

  5. University of Cantabria, Santander, Spain

    Akemi Galvez

  6. Nanyang Technological University, Singapore, Singapore

    Alexei Sourin

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Liu, Y., Hou, X., Sourina, O., Bazanova, O. (2016). Individual Theta/Beta Based Algorithm for Neurofeedback Games to Improve Cognitive Abilities. In: Gavrilova, M., Tan, C., Iglesias, A., Shinya, M., Galvez, A., Sourin, A. (eds) Transactions on Computational Science XXVI. Lecture Notes in Computer Science(), vol 9550. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49247-5_4

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  • DOI: https://doi.org/10.1007/978-3-662-49247-5_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49246-8

  • Online ISBN: 978-3-662-49247-5

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