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

Mengfan Li1,2,3, Enming Qi1,2,3, Guizhi Xu1,2,3

  • 1State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.

Cognitive Neurodynamics
|August 6, 2024
PubMed
Summary

Action sequence complexity and order significantly impact brain-computer interface (BCI) performance based on motor imagery (MI). Optimizing sequences enhances MI classification accuracy and provides new ERP-based performance metrics.

Keywords:
Action observationAction sequenceBrain-computer interfaceEvent-related potentialMotor imagery

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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.