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Moreover, this improvement has been shown to be effective, durable, and transferable (to skills that have not been subject to specific training) when the training duration is long enough. Finally, the user’s mental rotation ability seems to be a very good candidate to be trained, since this ability has been identified as a relevant predictor of BCI performance and since the consequences of mental rotation training on spatial and more general skills have been clearly identified. To conclude, we hope that this work will be useful to guide the design of new protocols and improve MI-BCI user-training so that these technologies become more accessible to their end-users.

Springer Science & Business Media. , 2015. Psychological factors influencing brain-computer interface (BCI) performance. In: Proceedings of the BCI Workshop of the SMC2015 Conference, pp. 3192–3196. , 2013. Motivation and SMR-BCI: fear of failure affects BCI performance. In: del R. E. ), Proceedings of the 5th International Brain-Computer Interface Meeting: Defining the Future, Asilomar Conference Center, Pacific Grove, California, USA, June 3–7, pp. 160–161. , 1980. Image and Mind. Harvard University Press, Cambridge.

Neurofeedback training for BCI control. , Allison, B. ), Brain-Computer Interfaces. Springer, Berlin, pp. 65–78. , 2005. Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG. Brain Res. Cogn. Brain Res. 25, 668–677. , 2008. An auditory brain-computer interface (BCI). J. Neurosci. Methods 167, 43–50. , 2010. The influence of psychological state and motivation on brain-computer interface performance in patients with amyotrophic lateral sclerosis—a longitudinal study.

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