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...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-01-01
|
| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2020.593854/full |
| _version_ | 1818971191669424128 |
|---|---|
| author | Halim I. Baqapuri Halim I. Baqapuri Linda D. Roes Linda D. Roes Mikhail Zvyagintsev Mikhail Zvyagintsev Souad Ramadan Souad Ramadan Micha Keller Micha Keller Erik Roecher Erik Roecher Jana Zweerings Jana Zweerings Martin Klasen Martin Klasen Ruben C. Gur Klaus Mathiak Klaus Mathiak |
| author_facet | Halim I. Baqapuri Halim I. Baqapuri Linda D. Roes Linda D. Roes Mikhail Zvyagintsev Mikhail Zvyagintsev Souad Ramadan Souad Ramadan Micha Keller Micha Keller Erik Roecher Erik Roecher Jana Zweerings Jana Zweerings Martin Klasen Martin Klasen Ruben C. Gur Klaus Mathiak Klaus Mathiak |
| author_sort | Halim I. Baqapuri |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-20T14:48:27Z |
| format | Article |
| id | doaj.art-f76c6ec2274b4e059e06fe2811b3cfde |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-20T14:48:27Z |
| publishDate | 2021-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-f76c6ec2274b4e059e06fe2811b3cfde2022-12-21T19:37:02ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2021-01-011410.3389/fnins.2020.593854593854A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRIHalim I. Baqapuri0Halim I. Baqapuri1Linda D. Roes2Linda D. Roes3Mikhail Zvyagintsev4Mikhail Zvyagintsev5Souad Ramadan6Souad Ramadan7Micha Keller8Micha Keller9Erik Roecher10Erik Roecher11Jana Zweerings12Jana Zweerings13Martin Klasen14Martin Klasen15Ruben C. Gur16Klaus Mathiak17Klaus Mathiak18Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyDepartment of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, GermanyJülich Aachen Research Alliance-Translational Brain Medicine, RWTH Aachen University, Aachen, GermanyVirtual 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.https://www.frontiersin.org/articles/10.3389/fnins.2020.593854/fullneurofeedback (NF)brain–computer interfaceself-regulationmethodology developmentvirtual environment (VE)real-time fMRI (rtfMRI) |
| spellingShingle | Halim I. Baqapuri Halim I. Baqapuri Linda D. Roes Linda D. Roes Mikhail Zvyagintsev Mikhail Zvyagintsev Souad Ramadan Souad Ramadan Micha Keller Micha Keller Erik Roecher Erik Roecher Jana Zweerings Jana Zweerings Martin Klasen Martin Klasen Ruben C. Gur Klaus Mathiak Klaus Mathiak A Novel Brain–Computer Interface Virtual Environment for Neurofeedback During Functional MRI Frontiers in Neuroscience neurofeedback (NF) brain–computer interface self-regulation methodology development virtual environment (VE) real-time fMRI (rtfMRI) |
| 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 | neurofeedback (NF) brain–computer interface self-regulation methodology development virtual environment (VE) real-time fMRI (rtfMRI) |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2020.593854/full |
| work_keys_str_mv | AT halimibaqapuri anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT halimibaqapuri anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT lindadroes anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT lindadroes anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT mikhailzvyagintsev anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT mikhailzvyagintsev anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT souadramadan anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT souadramadan anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT michakeller anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT michakeller anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT erikroecher anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT erikroecher anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT janazweerings anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT janazweerings anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT martinklasen anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT martinklasen anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT rubencgur anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT klausmathiak anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT klausmathiak anovelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT halimibaqapuri novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT halimibaqapuri novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT lindadroes novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT lindadroes novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT mikhailzvyagintsev novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT mikhailzvyagintsev novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT souadramadan novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT souadramadan novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT michakeller novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT michakeller novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT erikroecher novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT erikroecher novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT janazweerings novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT janazweerings novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT martinklasen novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT martinklasen novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT rubencgur novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT klausmathiak novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri AT klausmathiak novelbraincomputerinterfacevirtualenvironmentforneurofeedbackduringfunctionalmri |