sEEG-based brain-computer interfacing in a large adult and pediatric cohort

Objective. Stereoelectroencephalography (sEEG) is a mesoscale intracranial monitoring technique that records from the brain volumetrically with depth electrodes. sEEG is typically used for monitoring of epileptic foci, but can also serve as a useful tool to study distributed brain dynamics. Herein, we detail the implementation of sEEG-based brain-computer interfacing (BCI) across a diverse and large patient cohort.Approach. Across 27 subjects (15 female, 31 total feedback experiments), we identified channels with increases in broadband during hand, tongue, or foot movements using a simple block-design screening task. Subsequently, broadband power in these channels was coupled to continuous movement of a cursor on a screen during both overt movement and kinesthetic imagery.Main results. 26 subjects (29 out of 31 feedback conditions) established successful control, defined as more than 80 percent accuracy, during the overt movement BCI task, while only 12 (of the same 31 conditions) achieved control during the motor imagery BCI task. In successful imagery BCI, broadband power in the reinforced control channel(s) in the two target conditions separated into distinct subpopulations. Outside of the control channel(s), we demonstrate that imagery BCI engages unique subnetworks of the motor system compared to cued movement or kinesthetic imagery alone.Significance. Pericentral sEEG-based motor BCI utilizing overt movement and kinesthetic imagery is robust across a diverse patient cohort with inconsistent accuracy during imagined movement. Cued movement, kinesthetic imagery, and feedback engage the motor network uniquely, providing the opportunity to understand the network dynamics underlying BCI control and improve future BCIs.