Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

Abstract

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

Cracking the neural code, treating paralysis and the future of bioelectronic medicine

“…Furthermore, the participant was later able to think about static and dynamic/rhythmic movements, such as flexing and wiggling the finger or wrist, and switch between the two volitionally as shown in Fig. . These results exemplify what is possible with neural decoding and bioelectronic technology and are paving the way for applications in not only spinal cord injury, but potentially for stroke, traumatic brain injury, motor neuron disease and other areas in the future.…”

Clinically Significant Gains in Skillful Grasp Coordination by an Individual With Tetraplegia Using an Implanted Brain-Computer Interface With Forearm Transcutaneous Muscle Stimulation

“…This was a Phase I trial of a MEA-BCI interfaced with the Neurolife a transcutaneous, forearm FES. Like similar intracortical BCI studies, [12][13][14][15][16][17][18]35,36 this report was limited to 1 participant, the first to use the system, due to the invasive nature of the investigational brain implant and time required for training and assessment. Technical BCI-FES features 13,37 (fig 1), the Utah Array b MEA implantation procedures, and machine learning algorithms used to generate decoders were described previously.…”

“…Individuals with tetraplegia prioritize recovery of upper limb strength and dexterity to facilitate their independence. [1][2][3][4][5] Voluntary control of hand grasp has been restored to paralyzed limbs using noninvasive [6][7][8][9][10][11] and cortical microelectrode array (MEA)based [12][13][14][15][16] brain-computer interfaces (BCIs) that translate brain activity to hand movements evoked through implanted [10][11][12] or transcutaneous [6][7][8][9][13][14][15][16] functional electrical stimulation (FES). [6][7][8][9]12,13 However, clinically significant gains on tests of upper limb function have not been demonstrated using BCI-FES.…”

Restoring Movement in Paralysis with a Bioelectronic Neural Bypass Approach: Current State and Future Directions

“…These circuits are called central pattern generators (CPGs), which produce motor patterns for rhythmic movement (Marder and Bucher 2001). Recently, artificial CPGs have been created in software and linked to decoded brain activity sensed in primary motor cortex of a paralyzed human (Sharma et al 2016). In this work, CPG behavior was emulated by using a numerical model of an oscillatory neural circuit.…”