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A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI

Virtual environments (VEs), in the recent years, have become more prevalent in neuroscience. These VEs can offer great flexibility, replicability, and control over the presented stimuli in an immersive setting. With recent developments, it has become feasible to achieve higher-quality visuals and VE...

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Autores principales: Baqapuri, Halim I., Roes, Linda D., Zvyagintsev, Mikhail, Ramadan, Souad, Keller, Micha, Roecher, Erik, Zweerings, Jana, Klasen, Martin, Gur, Ruben C., Mathiak, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830095/
https://www.ncbi.nlm.nih.gov/pubmed/33505237
http://dx.doi.org/10.3389/fnins.2020.593854
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author Baqapuri, Halim I.
Roes, Linda D.
Zvyagintsev, Mikhail
Ramadan, Souad
Keller, Micha
Roecher, Erik
Zweerings, Jana
Klasen, Martin
Gur, Ruben C.
Mathiak, Klaus
author_facet Baqapuri, Halim I.
Roes, Linda D.
Zvyagintsev, Mikhail
Ramadan, Souad
Keller, Micha
Roecher, Erik
Zweerings, Jana
Klasen, Martin
Gur, Ruben C.
Mathiak, Klaus
author_sort Baqapuri, Halim I.
collection PubMed
description Virtual environments (VEs), in the recent years, have become more prevalent in neuroscience. These VEs can offer great flexibility, replicability, and control over the presented stimuli in an immersive setting. With recent developments, it has become feasible to achieve higher-quality visuals and VEs at a reasonable investment. Our aim in this project was to develop and implement a novel real-time functional magnetic resonance imaging (rt-fMRI)–based neurofeedback (NF) training paradigm, taking into account new technological advances that allow us to integrate complex stimuli into a visually updated and engaging VE. We built upon and developed a first-person shooter in which the dynamic change of the VE was the feedback variable in the brain–computer interface (BCI). We designed a study to assess the feasibility of the BCI in creating an immersive VE for NF training. In a randomized single-blinded fMRI-based NF-training session, 24 participants were randomly allocated into one of two groups: active and reduced contingency NF. All participants completed three runs of the shooter-game VE lasting 10 min each. Brain activity in a supplementary motor area region of interest regulated the possible movement speed of the player’s avatar and thus increased the reward probability. The gaming performance revealed that the participants were able to actively engage in game tasks and improve across sessions. All 24 participants reported being able to successfully employ NF strategies during the training while performing in-game tasks with significantly higher perceived NF control ratings in the NF group. Spectral analysis showed significant differential effects on brain activity between the groups. Connectivity analysis revealed significant differences, showing a lowered connectivity in the NF group compared to the reduced contingency-NF group. The self-assessment manikin ratings showed an increase in arousal in both groups but failed significance. Arousal has been linked to presence, or feelings of immersion, supporting the VE’s objective. Long paradigms, such as NF in MRI settings, can lead to mental fatigue; therefore, VEs can help overcome such limitations. The rewarding achievements from gaming targets can lead to implicit learning of self-regulation and may broaden the scope of NF applications.
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spelling pubmed-78300952021-01-26 A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI Baqapuri, Halim I. Roes, Linda D. Zvyagintsev, Mikhail Ramadan, Souad Keller, Micha Roecher, Erik Zweerings, Jana Klasen, Martin Gur, Ruben C. Mathiak, Klaus Front Neurosci Neuroscience Virtual environments (VEs), in the recent years, have become more prevalent in neuroscience. These VEs can offer great flexibility, replicability, and control over the presented stimuli in an immersive setting. With recent developments, it has become feasible to achieve higher-quality visuals and VEs at a reasonable investment. Our aim in this project was to develop and implement a novel real-time functional magnetic resonance imaging (rt-fMRI)–based neurofeedback (NF) training paradigm, taking into account new technological advances that allow us to integrate complex stimuli into a visually updated and engaging VE. We built upon and developed a first-person shooter in which the dynamic change of the VE was the feedback variable in the brain–computer interface (BCI). We designed a study to assess the feasibility of the BCI in creating an immersive VE for NF training. In a randomized single-blinded fMRI-based NF-training session, 24 participants were randomly allocated into one of two groups: active and reduced contingency NF. All participants completed three runs of the shooter-game VE lasting 10 min each. Brain activity in a supplementary motor area region of interest regulated the possible movement speed of the player’s avatar and thus increased the reward probability. The gaming performance revealed that the participants were able to actively engage in game tasks and improve across sessions. All 24 participants reported being able to successfully employ NF strategies during the training while performing in-game tasks with significantly higher perceived NF control ratings in the NF group. Spectral analysis showed significant differential effects on brain activity between the groups. Connectivity analysis revealed significant differences, showing a lowered connectivity in the NF group compared to the reduced contingency-NF group. The self-assessment manikin ratings showed an increase in arousal in both groups but failed significance. Arousal has been linked to presence, or feelings of immersion, supporting the VE’s objective. Long paradigms, such as NF in MRI settings, can lead to mental fatigue; therefore, VEs can help overcome such limitations. The rewarding achievements from gaming targets can lead to implicit learning of self-regulation and may broaden the scope of NF applications. Frontiers Media S.A. 2021-01-11 /pmc/articles/PMC7830095/ /pubmed/33505237 http://dx.doi.org/10.3389/fnins.2020.593854 Text en Copyright © 2021 Baqapuri, Roes, Zvyagintsev, Ramadan, Keller, Roecher, Zweerings, Klasen, Gur and Mathiak. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Baqapuri, Halim I.
Roes, Linda D.
Zvyagintsev, Mikhail
Ramadan, Souad
Keller, Micha
Roecher, Erik
Zweerings, Jana
Klasen, Martin
Gur, Ruben C.
Mathiak, Klaus
A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI
title A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI
title_full A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI
title_fullStr A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI
title_full_unstemmed A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI
title_short A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI
title_sort novel brain–computer interface virtual environment for neurofeedback during functional mri
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830095/
https://www.ncbi.nlm.nih.gov/pubmed/33505237
http://dx.doi.org/10.3389/fnins.2020.593854
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