Gamma band activity associated with BCI performance: simultaneous MEG/EEG study.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Brain-computer interfaces (BCI) offer communication and control for individuals with motor impairments.
• Motor imagery (MI) based BCIs are popular but suffer from user variability, termed 'BCI-Illiteracy', due to difficulties in modulating neural signals.
• The underlying mechanisms of BCI-Illiteracy and potential solutions are not well understood.

Purpose of the Study:

• To investigate the relationship between gamma-band neural activity and motor imagery (MI) performance in BCI users.
• To explore whether gamma activity can predict or explain individual differences in BCI performance and BCI-Illiteracy.

Main Methods:

• Simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recordings were performed on ten participants during MI tasks.
• EEG data were used to estimate MI performance.
• MEG data were analyzed to assess gamma-band activity, particularly in relation to BCI performance across subjects and sessions.

Main Results:

• A significant positive correlation was observed between gamma-band activity in the prefrontal cortex and MI performance.
• This correlation between gamma activity and performance was consistent both across different subjects and within individual subjects across multiple sessions.
• Higher gamma activity was associated with better BCI performance, suggesting a role in successful motor imagery modulation.

Conclusions:

• Gamma oscillations originating from the prefrontal cortex are critically involved in successful motor imagery BCI performance.
• Gamma activity may serve as a key neural marker for BCI proficiency and could offer insights into overcoming BCI-Illiteracy.
• Targeting or enhancing prefrontal gamma activity could be a potential strategy to improve BCI usability and accessibility.