An EEG-driven brain-computer interface combined with functional magnetic resonance imaging (fMRI)

Area of Science:

• Neuroscience
• Brain-Computer Interfaces
• Neuroimaging

Background:

• Self-regulation of slow cortical potentials (SCPs) is a validated method for seizure prevention and communication in paralyzed individuals.
• The thought translation device (TTD) facilitates SCP self-regulation training and application.
• Understanding the neurophysiological underpinnings of SCP regulation is crucial for advancing brain-computer interface (BCI) technologies.

Purpose of the Study:

• To investigate the neurophysiological mechanisms underlying SCP self-regulation.
• To explore the feasibility and technical considerations of combining TTD-based neurofeedback with functional magnetic resonance imaging (fMRI).

Main Methods:

• Integration of the TTD with fMRI for simultaneous data acquisition.
• EEG neurofeedback was employed to train SCP self-regulation within the fMRI environment.
• Discussion of technical challenges and solutions for combined fMRI and EEG neurofeedback.

Main Results:

• Presentation of initial data from SCP feedback during fMRI acquisition.
• Demonstration of the technical feasibility of combining TTD and fMRI.
• Insights into the neurophysiological processes involved in voluntary SCP modulation.

Conclusions:

• The combination of TTD and fMRI offers a powerful tool for elucidating the neurophysiology of SCP regulation.
• This integrated approach has implications for improving BCI applications in clinical and research settings.
• Further research is warranted to fully explore the potential of this methodology.