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

Abstract

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.

A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience

“…Although virtual interaction has not yet been seen in SP–NFT, it can be expected that the combination of the two technologies will make brain regulation more effective and help participants improve their sports performance. For example, Baqapuri et al (2021) found that the participants were engaged within the VR environment, improving their game performance over time while simultaneously employing NFT strategies. The study also pointed out that VR games can effectively slow down the reduction of participants’ training interest and maintain the NFT training effect ( Baqapuri et al, 2021 ).…”

“…For example, Baqapuri et al (2021) found that the participants were engaged within the VR environment, improving their game performance over time while simultaneously employing NFT strategies. The study also pointed out that VR games can effectively slow down the reduction of participants’ training interest and maintain the NFT training effect ( Baqapuri et al, 2021 ).…”

“…Among them, neurofeedback training (NFT), which refers to perception and learning of one’s own brain signals, is the most widely used technique in biofeedback. Further, NFT is not only the predecessor and an important part of the brain-computer interface (BCI) technology and an important aspect of neural engineering, but also one of the key technologies of brain–computer intelligent fusion ( Jeunet et al, 2018 ; Baqapuri et al, 2021 ).…”

Intelligent BCI Headphone for a Healthier and a Deeper Immersive Gameplay

“…Results from binary classification in the fre-International Journal of Intelligence Science quency domain with Alpha band gave the highest performance. A study done by Halim I. Baqapuri et al [26] has investigated the application of BCI gaming in virtual environment for neurofeedback training. A first-person shooter game was developed where the movement speed of the character was controlled by brain activity in a supplementary motor region of interest.…”

Applying antagonistic activation pattern to the single-trial classification of mental arithmetic

“…The technique that uses electrophysiological signals is electroencephalography (EEG), which records the electrical signals generated by the neuronal activity of the brain [ 9 , 10 ]. Non-invasive BCI for recording hemodynamic responses uses functional neuroimaging techniques, for example, functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) [ 11 , 12 , 13 , 14 ]. fMRI and fNIRS capture the changes in oxygen concentration in the blood consumed by neuronal activity in the brain and indirectly record neuronal activity.…”