High-Frequency Power Reflects Dual Intentions of Time and Movement for Active Brain-Computer Interface.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Active brain-computer interfaces (BCI) offer direct brain-device communication but have limited intention detection capabilities.
• Detecting dual intentions from a single electroencephalography (EEG) feature remains a significant challenge.

Purpose of the Study:

• To develop a time-based active BCI system.
• To investigate the feasibility of detecting simultaneous time and movement intentions using a single EEG feature.

Main Methods:

• A time-movement synchronization experiment was designed with time (500 ms vs. 1000 ms) and movement (left vs. right) intentions.
• Behavioral and EEG data were collected from 22 participants before and after timing prediction training.
• Analysis focused on event-related desynchronization (ERD) and event-related potentials (ERP) in high-frequency bands (20-60 Hz).

Main Results:

• Post-training sessions showed improved time decoding accuracy and enhanced motor-related brain activity.
• A single EEG feature (20-60 Hz power) demonstrated the ability to simultaneously represent both time and movement intentions.
• Achieved an average four-classification accuracy of 73.27% for dual intentions, with a maximum of 93.81%.

Conclusions:

• The study successfully verified the dual role of high-frequency (20-60 Hz) brain activity in representing both temporal and motor intentions.
• This research expands the detectable intentions for active BCI systems.
• The findings enable concurrent mind-reading from multiple information dimensions within BCI.