Enhancing visual brain-computer interface through V1-targeted RTMS by modulating visual attention

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Brain-computer interfaces (BCIs) offer direct control via brain activity but are limited by low signal-to-noise ratio (SNR).
• Neuromodulation techniques are crucial for overcoming SNR limitations and enhancing BCI decoding performance.

Purpose of the Study:

• To investigate if 5 Hz repetitive transcranial magnetic stimulation (rTMS) targeting the primary visual cortex (V1) improves SSVEP-based BCI performance.
• To assess the impact of rTMS on neural signal SNR and visual network dynamics.

Main Methods:

• Twenty-four healthy subjects received real or sham MRI-guided 5 Hz rTMS targeting V1.
• Electroencephalograms (EEGs) were recorded during steady-state visually evoked potential (SSVEP) tasks and resting-state.
• SSVEP tasks were performed across four frequency bands (LF, MF, HF, SHF).

Main Results:

• BCI command discriminability significantly improved in the middle (MF) and high frequency (HF) bands with real rTMS.
• Improved SNR was attributed to background activity suppression.
• rTMS enhanced visual attention, indicated by increased microstate B occurrence during SSVEP tasks.

Conclusions:

• 5 Hz rTMS is a potential neuromodulatory tool for optimizing BCI performance.
• Targeting V1 with rTMS enhances visual attention and neural signal quality, leading to better BCI decoding.
• This approach shows promise for advancing SSVEP-based BCI systems.