Moving intentions from brains to machines

Brain–computer interface (BCI) research has achieved remarkable technical progress but remains limited in scope, typically relying on motor and visual cortex signals in limited patient populations. We propose a paradigm shift in BCI design rooted in ideomotor theory, which conceptualizes voluntary action as driven by internally represented sensory outcomes. This underused framework offers a principled basis for next-generation BCIs that align closely with the brain’s natural intentional and action-planning architecture. We suggest a more intuitive, generalizable, and scalable path by reorienting BCIs around the ‘what for’ of action—user goals and anticipated effects. This shift is timely and feasible, enabled by advances in neural recording and artificial intelligence–based decoding of sensory representations. It may help resolve challenges of usability and generalizability in BCI design.