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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
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A Novel Brain-Computer Interface Virtual Environment for Neurofeedback During Functional MRI.

Halim I Baqapuri1,2, Linda D Roes1,2, Mikhail Zvyagintsev1,2

  • 1Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany.

Frontiers in Neuroscience
|January 28, 2021
PubMed
Summary
This summary is machine-generated.

This study developed a novel neurofeedback (NF) system using virtual environments (VEs) and real-time fMRI. The system enhanced immersion and self-regulation skills in participants playing a video game.

Keywords:
brain–computer interfacemethodology developmentneurofeedback (NF)real-time fMRI (rtfMRI)self-regulationvirtual environment (VE)

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Area of Science:

  • Neuroscience
  • Human-Computer Interaction
  • Cognitive Science

Background:

  • Virtual environments (VEs) offer enhanced control and immersion for neuroscience research.
  • Real-time functional magnetic resonance imaging (rt-fMRI) enables direct brain activity monitoring.
  • Integrating VEs with rt-fMRI neurofeedback (NF) presents opportunities for novel training paradigms.

Purpose of the Study:

  • To develop and implement a novel rt-fMRI-based neurofeedback (NF) training paradigm using an engaging virtual environment (VE).
  • To assess the feasibility of a brain-computer interface (BCI) within a first-person shooter VE for NF training.
  • To investigate the effects of NF on brain activity, connectivity, and self-reported immersion.

Main Methods:

  • A randomized single-blinded study involving 24 participants in active and reduced contingency NF groups.
  • Participants engaged in a 10-minute rt-fMRI-compatible first-person shooter VE for three runs.
  • Brain activity in the supplementary motor area regulated avatar movement speed and reward probability, serving as the BCI feedback.

Main Results:

  • Participants demonstrated improved gaming performance and higher perceived NF control in the active NF group.
  • Spectral analysis revealed significant differences in brain activity between the groups.
  • Connectivity analysis indicated lowered functional connectivity in the active NF group compared to the reduced contingency group.

Conclusions:

  • The developed VE-BCI-NF system is feasible for immersive training and enhances self-regulation.
  • VEs can mitigate mental fatigue associated with prolonged fMRI NF paradigms.
  • This approach broadens the scope of NF applications through implicit learning and rewarding gaming achievements.