Abstract
Studies using BCIs based upon non-invasive, scalp recorded electroencephalography (EEG) have consistently demonstrated utility, both as scientific tools for neuromodulation and for clinical neurorehabilitation purposes. They are particularly appealing in clinical contexts where physical movement is impaired, for instance following stroke. The intrinsic advantage of Brain-Computer Interfaces (BCIs) over alternate rehabilitation strategies is that they work even when output at the behavioural level is non-existent. Patients exhibiting minimal or no residual limb movement after a stroke cannot partake in gold standard physiotherapy, but might still demonstrate brain activity patterns when attempting to move the impaired limb. These patterns can be targeted to enhance recovery. However, the role of BCI should evolve once behavioural output is available. We must not be seduced by the allure of cutting-edge technology at the expense of targeting the specific neurophysiological features that are most likely to drive recovery. At the most basic mechanistic level, the majority of BCIs are driven by neural signals generated by imagination of movement. We need to revisit the question—could motor imagery alone could achieve the same outcomes, or what is the added clinical benefit of the BCI? Accordingly, what is the minimum required intervention using BCI (in terms of time and hardware) to establish a habit of good quality motor imagery that could then sustain rehabilitation without the technology? Motor imagery is free, available to every person and at any time. Using technology to harness its virtues while not compromising its simplicity is the ultimate challenge for the field.
Technology is the answer. But what was the question?
Cedric Price (1966)
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Simon, C., Ruddy, K. (2024). Keeping Our Eyes on the Prize; Are We Losing Sight of the ‘Why’ in BCI for Neurorehabilitation?. In: Guger, C., Allison, B., Rutkowski, T.M., Korostenskaja, M. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-49457-4_8
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