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Abstract #1418

GRL-MF: The first lego-brick of a cerebellar Mean-Field Model for BOLD signal simulations

Roberta Maria Lorenzi1, Alice Geminiani1, Claudia AM Gandini Wheeler-Kingshott1,2,3, Fulvia Palesi1, Claudia Casellato1, and Egidio D'Angelo1,3
1Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy, 2NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, UCL, London, United Kingdom, 3Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy


Following MRI recordings, the connectome can be reconstructed and BOLD-signals simulated extracting relevant parameters on brain organization and dynamics. This requires mathematical models of neural activity in specific brain regions. However, models of the cerebellar circuit are still missing. We present here a biologically-driven mean-field (MF) model summarising the main statistical moments of cerebellar granular layer activity as the first “lego-brick” toward full cerebellar network reconstruction. Once integrated into brain simulators, like Dynamic Causal Modelling and The Virtual Brain, the cerebellar MF models will improve the investigation of neuronal functions at the origin of hemodynamic responses captured by BOLD fMRI.

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