Cortically controlled brain-machine interface.

Over the past ten years, we have tested and helped develop a multi-electrode array for chronic cortical recordings in behaving non-human primates. We have found that it is feasible to record from dozens of single units in the motor cortex for extended periods of time and that these signals can be decoded in a closedloop, real-time system to generate goal-directed behavior of external devices. This work has culminated in a FDA clinical trial that has demonstrated that a tetraplegic patient can voluntarily modulate motor cortical activity in order to move a computer cursor to visual targets. Further advances in BMI technology using non-human primates have focused on using multiple modes of control from signals in different cortical areas. We demonstrate that primary motor cortical activity may be optimized for continuous movement control whereas signals from the premotor cortex may be better suited for discrete target selection. We propose a hybrid BMI whereby decoding can be voluntarily switched from discrete to continuous control modes.