PT - JOURNAL ARTICLE AU - Emanuele Formento AU - Paul Botros AU - Jose M. Carmena TI - A non-invasive brain-machine interface via independent control of individual motor units AID - 10.1101/2021.03.22.436518 DP - 2021 Jan 01 TA - bioRxiv PG - 2021.03.22.436518 4099 - http://biorxiv.org/content/early/2021/03/23/2021.03.22.436518.short 4100 - http://biorxiv.org/content/early/2021/03/23/2021.03.22.436518.full AB - Brain-machine interfaces (BMIs) have the potential to restore independence in people with disabilities, yet a compromise between non-invasiveness and performance limits their translational relevance. Here, we demonstrate a high-performance BMI controlled by individual motor units non-invasively recorded from the biceps brachii. Through real-time auditory and visual neurofeedback of motor unit activity, 8 participants learned to skillfully and independently control three motor units in order to complete a two-dimensional center-out task, with marked improvements in control over 6 days of training. Concomitantly, dimensionality of the motor unit population increased significantly relative to naturalistic behaviors, largely violating recruitment orders displayed during stereotyped, isometric muscle contractions. Finally, participants’ performance on a spelling task demonstrated translational potential of a motor unit BMI, exceeding performance across existing non-invasive BMIs. These results demonstrate a yet-unexplored level of flexibility of the peripheral sensorimotor system and show that this can be exploited to create novel non-invasive, high-performance BMIs.Competing Interest StatementE.F. and P.B. acted as participants of the study. E.F., P.B., and J.M.C. hold a patent related to the proposed motor unit brain-machine interface.