Sensory Restoration via Brain-Computer Interfaces: A Unified 2 x 2 Framework and Convergence Roadmap

The article proposes a unified 2 x 2 framework for categorizing brain-computer interfaces (BCIs) based on invasiveness and signal direction, addressing the fragmentation in the field between invasive neuroprosthetics and non-invasive decoders. It defines key paradigms such as restoration, substitution, and augmentation, and outlines a convergence roadmap that emphasizes the role of machine learning foundation models in advancing BCI technology. This framework is significant for practitioners as it provides a structured approach to compare and develop BCI systems, potentially enhancing sensory and motor restoration techniques.