Mixture-of-Microzones for slow and fast sensorimotor adaptation

Learning in naturalistic environments requires both rapid and long-term sensorimotor adaptation. How the brain and machines achieve such dual control is not clear. We introduce Mixture-of-Microzones (MoM), a cerebellar-inspired architecture that separates immediate error correction from slower learning. MoM uses error geometry to sparsely recruit specialized modules according to error direction and magnitude. Recruited modules perform local, state-conditioned coordinate transformations from sensory-error space to motor space, allowing their corrections to be composed and applied directly to the controller output. In parallel, the same gate determines which modules receive learning updates, progressively consolidating the response. In sensorimotor adaptation, this structured corrective pathway reduces adaptation time by approximately fourfold relative to ablated variants and substantially outperforms existing controller–adapter baselines. Ablations show that neither geometric gating nor a direct corrective pathway alone is sufficient: their combination is required to produce appropriately aligned motor corrections and rapid adaptation. We further isolate this principle in learned optimization, where directional gating generalizes to unseen coordinate transformations. Together, these results identify error-geometric coordinate transformation as a mechanism for correcting perturbations immediately while slower adaptive processes consolidate the response.