The shifting role of the cerebellum in executive, emotional and social processing across the lifespan

International audienceAbstract The cerebellum’s anatomical and functional organization and network interactions between the cerebellum and the cerebral cortex and subcortical structures are dynamic across the lifespan. Executive, emotional and social (EES) functions have likewise evolved during human development from contributing to primitive behaviors during infancy and childhood to being able to modulate complex actions in adults. In this review, we address how the importance of the cerebellum in the processing of EES functions might change across development. This evolution is driven by the macroscopic and microscopic modifications of the cerebellum that are occurring during development including its increasing connectivity with distant supra-tentorial cortical and sub-cortical regions. As a result of anatomical and functional changes, neuroimaging and clinical data indicate that the importance of the role of the cerebellum in human EES-related networks shifts from being crucial in newborns and young children to being only supportive later in life. In early life, given the immaturity of cortically mediated EES functions, EES functions and motor control and perception are more closely interrelated. At that time, the cerebellum due to its important role in motor control and sequencing makes EES functions more reliant on these computational properties that compute spatial distance, motor intent, and assist in the execution of sequences of behavior related to their developing EES expression. As the cortical brain matures, EES functions and decisions become less dependent upon these aspects of motor behavior and more dependent upon high-order cognitive and social conceptual processes. At that time, the cerebellum assumes a supportive role in these EES-related behaviors by computing their motor and sequential features. We suspect that this evolving role of the cerebellum has complicated the interpretation of its contribution to EES computational demands