Concurrent control of a brain-computer interface and natural overt movements.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Brain-computer interfaces (BCIs) traditionally rely on movement-related cortical signals.
• Concurrent BCI and natural movement control presents challenges due to potential signal interference.
• Existing BCIs may limit natural motor function when used simultaneously.

Purpose of the Study:

• To investigate if the brain can learn to control both a BCI and concurrent overt movements independently.
• To explore the dissociation of neural control signals from their associated motor behaviors.
• To assess the feasibility of simultaneous BCI and natural limb movement coordination.

Main Methods:

• Experiments designed for concurrent BCI and overt movement control in a 2D task.
• Utilized 70-90 Hz band power from human electrocorticography (ECoG) signals for BCI control.
• Recorded ECoG signals from cortical sites associated with both BCI and overt finger movements.

Main Results:

• Three subjects successfully performed concurrent BCI and natural movement tasks.
• Demonstrated simultaneous and largely independent control of BCI and natural movements.
• Showcased the brain's ability to dissociate control signals from associated behaviors.

Conclusions:

• The brain can learn to generate distinct BCI control signals during ongoing overt movements.
• Cortical activity can be dissociated from its originally associated behavior.
• Simultaneous control of devices via BCI alongside natural limb movements is feasible.