A delayed matching task-based study on action sequence of motor imagery

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Brain-computer interfaces (BCI) utilizing motor imagery (MI) are sensitive to cognitive factors.
• Action sequences are fundamental to motor behavior, but their influence on MI-BCI remains unclear.

Purpose of the Study:

• To investigate how action sequence complexity and order affect MI-BCI performance.
• To develop a novel paradigm for observing and reinforcing action sequence memory.
• To identify new electroencephalography (EEG)-based metrics for MI performance.

Main Methods:

• A novel 'action sequences observing and delayed matching task' paradigm was developed using visual stimuli (images and videos).
• Electroencephalography (EEG) recordings, specifically event-related potentials (ERPs), and MI performance were analyzed in seven subjects.
• Participants were exposed to action sequences of varying complexity and order (positive vs. negative).

Main Results:

• Action sequence complexity and order significantly influenced MI.
• Complex actions in positive order led to stronger ERD/ERS and clearer MI feature distributions.
• MI classification accuracy was 12.3% higher for complex positive-order sequences compared to negative-order sequences (p < 0.05).
• ERP amplitudes from the supplementary motor area correlated positively with MI performance.

Conclusions:

• Action sequence characteristics (complexity and order) are crucial for optimizing MI-BCI.
• The proposed paradigm and ERP-based index offer a novel approach to assessing and enhancing MI.
• This research provides a new perspective for improving MI-BCI by considering cognitive factors related to motor sequences.