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Brain-computer interfaces (BCIs) allow control of applications or external devices solely by brain activity, measured by different neuroimages techniques, e.g., EEG or fNIRS. Some users are unable to modulate their brain activity sufficiently to control a BCI. Most of the studies have focused on improving BCI performance accuracy through advances in signal processing and BCI protocol modification. However, some research suggests that individual differences in cognitive, psychological, and physiological factors may modify BCI performance. The results of our previous studies show that factors such as attention, motivation [1], temperament [2], imagery skills, or movement experiences [3] can significantly affect the effectiveness of brain-computer communication. Consequently, we would like to discuss these findings' implications on the design of future BCIs and po ssibly new research directions.

[1] Zapała, D., Francuz, P., Zapała, E., Kopiś, N., Wierzgała, P., Augustynowicz, P., ... & Kołodziej, M. (2018). The impact of different visual feedbacks in user training on motor imagery control in BCI. Applied psychophysiology and biofeedback, 43(1), 23-35.
[2] Zapała, D., Małkiewicz, M., Francuz, P., Kołodziej, M., & Majkowski, A. (2019). Temperament Predictors of Motor Imagery Control in BCI. Journal of Psychophysiology.
[3] Zapała, D., Zabielska-Mendyk, E., Augustynowicz, P., Cudo, A., Jaśkiewicz, M., Szewczyk, M., ... & Francuz, P. (2020). The effects of handedness on sensorimotor rhythm desynchronization and motor-imagery BCI control. Scientific reports, 10(1), 1-11.