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Designing brain-computer interfaces (BCIs) that can be used in conjunctionwith ongoing motor behavior requires an understanding of how neural activityco-opted for brain control interacts with existing neural circuits. Forexample, BCIs may be used to regain lost motor function after stroke. Thisrequires that neural activity controlling unaffected limbs is dissociated fromactivity controlling the BCI. In this study we investigated how primary motorcortex accomplishes simultaneous BCI control and motor control in a task thatexplicitly required both activities to be driven from the same brain region(i.e. a dual-control task). Single-unit activity was recorded fromintracortical, multi-electrode arrays while a non-human primate performed thisdual-control task. Compared to activity observed during naturalistic motorcontrol, we found that both units used to drive the BCI directly (controlunits) and units that did not directly control the BCI (non-control units)significantly changed their tuning to wrist torque. Using a measure ofeffective connectivity, we observed that control units decrease theirconnectivity. Through an analysis of variance we found that the intrinsicvariability of the control units has a significant effect on task proficiency.When this variance is accounted for, motor cortical activity is flexible enoughto perform novel BCI tasks that require active decoupling of naturalassociations to wrist motion. This study provides insight into the neuralactivity that enables a dual-control brain-computer interface.

Reconfiguring motor circuits for a joint manual and BCI task