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.