Bionic Vision as Neuroadaptive XR: Closed-Loop Perceptual Interfaces for Neurotechnology (2508.05963v1)

Abstract: Visual neuroprostheses are commonly framed as technologies to restore natural sight to people who are blind. In practice, they create a novel mode of perception shaped by sparse, distorted, and unstable input. They resemble early extended reality (XR) headsets more than natural vision, streaming video from a head-mounted camera to a neural "display" with under 1000 pixels, limited field of view, low refresh rates, and nonlinear spatial mappings. No amount of resolution alone will make this experience natural. This paper proposes a reframing: bionic vision as neuroadaptive XR. Rather than replicating natural sight, the goal is to co-adapt brain and device through a bidirectional interface that responds to neural constraints, behavioral goals, and cognitive state. By comparing traditional XR, current implants, and proposed neuroadaptive systems, it introduces a new design space for inclusive, brain-aware computing. It concludes with research provocations spanning encoding, evaluation, learning, and ethics, and invites the XR community to help shape the future of sensory augmentation.