Search

Background: Information transmission into the human nervous system is the basis for a variety of prosthetic applications. Spinal cord stimulation (SCS) systems are widely available, have a well documented safety record, can be implanted minimally invasively, and are known to stimulate afferent pathways. Nonetheless, SCS devices are not yet used for computer-brain-interfacing applications. Objective: Here we aimed to establish computer-to-brain communication via medical SCS implants in a group of 20 individuals who had been operated for the treatment of chronic neuropathic pain. Methods: In the initial phase, we conducted interface calibration with the aim of determining personalized stimulation settings that yielded distinct and reproducible sensations. These settings were subsequently utilized to generate inputs for a range of behavioral tasks. We evaluated the required calibration time, task training duration, and the subsequent performance in each task. Results: We could establish a stable spinal computer-brain interface in 18 of the 20 participants. Each of the 18 then performed one or more of the following tasks: A rhythm-discrimination task (n = 13), a Morse-decoding task (n = 3), and/or two different balance/body-posture tasks (n = 18; n = 5). The median calibration time was 79 min. The median training time for learning to use the interface in a subsequent task was 1:40 min. In each task, every participant demonstrated successful performance, surpassing chance levels. Conclusion: The results constitute the first proof-of-concept of a general purpose computer-brain interface paradigm that could be deployed on present-day medical SCS platforms.

Abstract Sensory substitution offers a promising approach to restore lost sensory functions. Here we show that spinal cord stimulation (SCS), typically used for chronic pain management, can potentially serve as a novel auditory sensory substitution device. We recruited 13 patients undergoing SCS implantation and translated everyday sound samples into personalized SCS patterns during their trial phase. In a sound identification task—where chance-level performance was 33.3%—participants ( $$n=8$$ n = 8 ) achieved a mean accuracy of 72.8% using only SCS input. We observed a weak positive correlation between stimulation bitrate and identification accuracy. A follow-up discrimination task ( $$n=5$$ n = 5 ) confirmed that reduced bitrates significantly impaired participants’ ability to distinguish between consecutive SCS patterns, indicating effective processing of additional information at higher bitrates. These findings demonstrate the feasibility of using existing SCS technology to create a novel neural interface for a sound prosthesis. Our results pave the way for future research to enhance stimulation fidelity, assess long-term training effects, and explore integration with other auditory aids for comprehensive hearing rehabilitation.