Brain computer interfaces for human motor- cognitive enhancement
I discuss two models of BCi that correlate to neural error detection and to enhanced motor memory consolidation, then apply to a three tier model of applied BCI for enhanced human relearning of motor skills such as after stroke, accidents or in general a BCI system for motor learning.
Three components are embedded in relearning of motor skills: brain signals of error detection, training to reduce errors, and memory consolidation of the improved motor execution. I integrate here three components that I have previously studied separately, into a triple-stage paradigm that includes EEG markers for error detection, BCI-based motor correction and BCI for memory consolidation of the corrected motor motion through neurofeedback processes. In my earlier work I show that error potentials are uniquely associated with error characteristics, suggesting a potential BCI system for error-tailored correction, rather than generic BCI. The third component relates to neurofeedback. My earlier studies of neurofeedback theta after motor learning, showed a significant effect of enhanced motor memory consolidation in the experimental group compared to the control groups. Here I describe a preliminary three stage protocol of motor rehabilitation: error detection, BCI for motor correction and then a neurofeedback for consolidation of the corrected motion.