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Abstract #3132

Cerebellum integration in motor network improves Dynamic Causal Modeling performance

Roberta Maria Lorenzi1, Letizia Casiraghi1,2, Adnan Alahmadi3,4, Anita Monteverdi1,5, Egidio D'Angelo1,5, Fulvia Palesi1,5, and Claudia A.M. Gandini Wheeler-Kingshott1,4,5
1Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, 2Azienda Socio Sanitaria Territoriale (ASST) di Pavia, Pavia, Italy, 3Department of Diagnostic Radiology, College of Applied medical sciences, King Abdulaziz University, Jeddah, Saudi Arabia, 4NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, United Kingdom, 5Brain Connectivity Centre Research Department, IRCCS Mondino Foundation, Pavia, Italy

Dynamic Causal Modelling (DCM) is a framework enabling to quantify the causal relationship between functionally connected regions of the brain. Here we investigate cerebellum role in motion generation by adding a cerebellar node to an already validated motor network. We assessed how this operation improved DCM fMRI prediction. First- and second-level analyses were performed and the network including the cerebellum predicted the observed data with higher efficiency at single subject and group level. This network is important to study people with motor impairment where one could compare DCM predictions in heathy subjects and patients.

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