Rapid learning and integration of artificial sensation

Prosthetic limbs lack proprioceptive feedback, which is essential for complex movements. Intracortical mi-crostimulation (ICMS) elicits sensory perceptions that could serve as an artificial proprioceptive signal. However, movements guided by ICMS are slower and less accurate than those with natural sensation. Here, we developed a freely-moving mouse behavioral task to improve ICMS encoding of artificial sensation. Mice implanted with 16-channel microwire arrays in primary somatosensory cortex were trained to navigate to targets upon the floor of a custom behavioral training cage. Target location was encoded with visual and/or ICMS feedback. Mice quickly learned to use the ICMS signal to locate invisible targets, achieving 75% proficiency on ICMS-only trials by the first three sessions of testing. Furthermore, performance on multimodal trials significantly exceeded unimodal performance, demonstrating that animals integrated natural vision with artificial sensation. This protocol can be applied to efficiently develop and test algorithms to encode artificial proprioception for neural prostheses.