Performance of motor imagery brain-computer interface based on anodal transcranial direct current stimulation...

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Brain-computer interfaces (BCIs) typically rely on user-trained neural modulation for control.
• Repetitive feedback training in BCI systems can be time-consuming and may limit performance.
• Investigating external methods to directly modulate neural activity could improve BCI efficiency.

Purpose of the Study:

• To explore if anodal transcranial direct current stimulation (tDCS) can facilitate BCI control.
• To assess the impact of tDCS-induced electroencephalography (EEG) pattern changes on BCI classification accuracy.
• To determine if external modulation can accelerate the development of effective BCI control strategies.

Main Methods:

• An experimental paradigm combining anodal tDCS with a motor imagery (MI)-based feedback EEG BCI system was designed.
• Thirty-two healthy subjects were randomly assigned to real tDCS or sham stimulation groups.
• EEG data was analyzed to evaluate tDCS effects on sensorimotor rhythm (SMR) and event-related desynchronization (ERD) patterns.

Main Results:

• Anodal tDCS significantly altered SMR-related ERD patterns in the upper-mu (10-14 Hz) and beta (14-26 Hz) frequency bands.
• Both online and offline BCI classification results indicated performance improvements.
• Enhanced ERD patterns were conditionally associated with improved BCI performance.

Conclusions:

• Transcranial direct current stimulation (tDCS) shows promise as an external method to modulate neural activity for BCI applications.
• tDCS can induce beneficial changes in EEG patterns, potentially enhancing BCI control.
• This approach may enable users to develop reliable BCI control strategies more rapidly.