Data from: Investigating the impact of feedback update interval on efficacy of restorative brain-computer interfaces

Restorative brain-computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite promising results from early studies, reaching clinically significant outcomes in a timely fashion is yet to be achieved. This lack of efficacy may be due to sub-optimal feedback provision. To our knowledge, the optimal feedback update interval (FUI) during MI remains unexplored. There is evidence that sensory feedback disinhibits the motor cortex. Thus in this study we explore how shorter than usual FUIs affect behavioural and neurophysiological measures following BCI training for stroke patients using a single case proof-of-principle study design. The action research arm test (ARAT) was used as the primary behavioural measure and showed a clinically significant increase (36%) over the course of training. The neurophysiological measures including motor evoked potentials (MEP) and maximum voluntary contraction (MVC) showed distinctive changes in early and late phases of BCI training. Thus, this preliminary study may pave the way for running larger studies to further investigate the effect of FUI magnitude on the efficacy of restorative BCIs. It may also provide implications regarding the role of early and late phases of motor learning along the course of BCI training.