A Wireless Self-Fine-Tuning Artificial Neural Pathway Implant for Near-Real-Time Close-Loop Motor Modulation

Artificial neural pathway (ANP) implants hold transformative potential for empowering individuals with disabilities, which has recently revolutionized the clinical treatment of spinal cord injury through epidural electrical stimulation (EES). Classical EES operates with a pre-set program and needs manual modification, consuming both manpower and time. Although existed studies proposed kinematic image processing to configurate EES or a brain-spine interface to control motions automatically, prompt tuning on motor modulation in an open environment is still inaccessible. Here, we show a wireless self-fine-tuning ANP implant to establish a rapid self-feedback mechanism appropriate for free activities to achieve precise motor modulation by EES. The fine-tuning pathway was attached to the writing pathway using a wireless implanted bidirectional neural interface featuring compact size, low input noise, and high energy efficiency, with different functionalities including reading, writing, and bidirectional control. The sciatic neural signals are fed into the pathway as rapid feedback for self tuning. Without manual interventions, we restored gaits of hindlegs in paralyzed animals with EES by a self-fine-tuning, near-real-time, and close-loop motor modulation mechanism.