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2016 | OriginalPaper | Chapter

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

Authors : Yisi Liu, Xiyuan Hou, Olga Sourina, Olga Bazanova

Published in: Transactions on Computational Science XXVI

Publisher: Springer Berlin Heidelberg

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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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Metadata
Title
Individual Theta/Beta Based Algorithm for Neurofeedback Games to Improve Cognitive Abilities
Authors
Yisi Liu
Xiyuan Hou
Olga Sourina
Olga Bazanova
Copyright Year
2016
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-49247-5_4

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