Coordinated cerebellar climbing fiber activity signals learned sensorimotor predictions.

The prevailing model of cerebellar learning states that climbing fibers (CFs) are both driven by, and serve to correct, erroneous motor output. However, this model is grounded largely in studies of behaviors that utilize hardwired neural pathways to link sensory input to motor output. To test whether this model applies to more flexible learning regimes that require arbitrary sensorimotor associations, we developed a cerebellar-dependent motor learning task that is compatible with both mesoscale and single-dendrite-resolution calcium imaging in mice.