Dynamic Causal Modelling(DCM) is a framework enabling the quantification of the causal relationship between functionally connected brain regions. Here we included the cerebellum in a visuomotor network to investigate its role in motion prediction and how different Grip-Force levels modulate the effective connectivity between cerebellum and primary visual cortex. We estimated different DCMs models and we used Bayesian Models Selection to assess the best model at group-level. This study paves the way for investigating the source of BOLD non-linearities when applying different grip-forces in terms of modulations of the cerebro-cerebellar connections.
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