Brain connectivity evaluation during selective attention using EEG-based brain-computer interface

ABSTRACT

Attentional deficits may be caused by neurological diseases, including Attention-Deficit/Hyperactivity Disorder (ADHD), Alzheimer’s disease (AD), Traumatic Brain Injuries (TBI), etc. This work aims to evaluate selective attention under visual stimulations of faces and scenes using electroencephalogram (EEG)-based brain-computer interface.The experiment consisted of two phases: 1) image recognition and 2) attention evaluation. In phase 1, the mean response time was 547 ms vs. 633 ms to faces and scenes, respectively. In phase 2, the mean response time was 667 ms vs. 706 ms to face and scene categories, respectively. We analyzed the event-related time-frequency representation of faces and scenes and the causal relationship between object recognition and the motor response associated with category selection using the brain connectivity based on Granger causality. The developed experimental protocols and connectivity evaluation methods may provide insights for a better understanding of the neural processes for object recognition and category selection.

KEYWORDS:

• Brain-computer interface
• selective attention
• EEG
• event-related potential
• Granger Causality
• time-frequency
• brain connectivity

Acknowledgments

We greatly thank Makoto Miyakoshi for his helpful comments on the preprocessing pipeline.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was in part supported by Alzheimer's Tennessee, by the National Institutes of Health under grant numbers 5P30AG028383 and UL1TR000117, and by the National Science Foundation through Research Experience for Undergraduates (REU) award no. 1659502.