Restoring cortical control of functional movement in a human with quadriplegia

Abstract

Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic 'neural bypass' to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant's forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5-C6) to the seventh cervical to first thoracic (C7-T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.

Closed-loop brain training: the science of neurofeedback

“…Recently, human BMIs have shown that learned control of multiple neurons can operate different types of external devices to facilitate communication and motor control in people with paralysis. For example, on the basis of activity in the primary motor cortex (M1) recorded from intracortical multielectrode arrays, individuals with partial paralysis were able to learn coordinated movements of a seven degrees-of-freedom robotic arm 13 , to control a computer cursor 14 or to functionally stimulate muscles 15 .…”

Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation

“…The neuromuscular system can be interfaced at various levels to extract neural signals that code the intended movement, e.g., via brain, nerve or muscle recordings [4][5][6][7][8][9] . Although direct brain signal decoding provides the neural information associated to movement intention and control [10][11][12] , peripheral approaches (nerves or muscles) are so far the only clinically viable solutions for re-establishing upper limb function in amputees 4,13 . In these patients, the availability of nerve and muscle structures above the amputation allows access to neural information at the output of the spinal cord circuitries.…”

Evaluation of Muscle Strength in Medullar Injury: A Literature Review

“…Application of the motor subtest of the GRASSP tool was confirmed in four studies. 9,24,51,58 It evaluates the upper limbs through MMT on a scale of six points. 26 The modified Brunstron and Dennem grading scale was applied in three studies.…”