Computational NeurosciencePerformance variation in motor imagery brain-computer interface: A brief review

- We provide here a comprehensive literature review of performance variation in BCI.
- Low-performance groups have a less-developed brain network for motor imagery.
- We propose a possible strategic model to deal with performance variation.
- Intra-subject and clinical studies of patients are significant, but lacking.
- Integrative studies among several types of variables are required for better understanding.

Brain-computer interface (BCI) technology has attracted significant attention over recent decades, and has made remarkable progress. However, BCI still faces a critical hurdle, in that performance varies greatly across and even within subjects, an obstacle that degrades the reliability of BCI systems. Understanding the causes of these problems is important if we are to create more stable systems. In this short review, we report the most recent studies and findings on performance variation, especially in motor imagery-based BCI, which has found that low-performance groups have a less-developed brain network that is incapable of motor imagery. Further, psychological and physiological states influence performance variation within subjects. We propose a possible strategic approach to deal with this variation, which may contribute to improving the reliability of BCI. In addition, the limitations of current work and opportunities for future studies are discussed.