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On one side are those who seek to identify a universal cerebellar transform, a single algorithm that can be applied across domains as diverse as sensorimotor learning, social cognition, and decision-making. On the other side are those who focus on functional specializations tailored for different task domains. In this perspective, we propose an integrated approach, one that recognizes functional specialization across different cerebellar subregions, but also builds on common constraints that help define the conditions that engage the cerebellum. Drawing on recurring principles from the cerebellum\u2019s well-established role in motor control, we identify three core constraints: 1) Prediction\u2014the cerebellum performs anticipatory, simulation-based computations; 2) Timescale\u2014the cerebellum generates predictions limited to short intervals; and 3) Continuity\u2014the cerebellum facilitates the manipulation of mental representations in a continuous, but not discrete manner. 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