ABSTRACT
There are still many obstacles that must be solved before brain–computer interfaces (BCIs) can advance out of controlled research settings and into real-world scenarios. Some of these obstacles arise because of a growing separation between neuroscience and neuroengineering. Much of modern neuroscience research operates at the cortical level, so it is difficult to leverage this basic science research in BCIs that use noninvasive recordings (e.g., electroencephalography or magnetoencephalography) because those BCI data are recorded from outside the head. A neuroimaging technique called “source imaging” may offer a way to alleviate this disconnect as it allows the estimation cortical activity (on the surface of the brain) from noninvasive data (recorded on or above the surface of the scalp). We start by explaining the fundamentals of source imaging and then explore research using this technique to address two issues in BCI research. First, targeting brain activity from the most relevant cortical region can improve classification accuracy compared to the traditional approach. Second, source imaging was shown to improve transfer learning—an area of research aimed at reducing the 20- to 30-min calibration period required for most noninvasive BCIs. Overall, this chapter illustrates how tools and research findings from neuroscience can serve as a principled way to advance BCI methodology.
