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Abstract #2699

Biologically-driven cerebellar neural mass model for improving BOLD signal simulations

Roberta Maria Lorenzi1, Alice Geminiani1, Claudia A.M. Gandini Wheeler-Kingshott1,2,3, Fulvia Palesi1,3, Claudia Casellato1, and Egidio D'Angelo1,3
1Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, 2NMR 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, 3Brain Connectivity Centre Research Department, IRCCS Mondino Foundation, Pavia, Italy

Whole-brain activity can be simulated as a collection of BOLD signals by solving mathematical models representing neuronal circuitry organization of different brain regions. The cerebellum strongly contributes to the whole-brain dynamics. We present the formalism for a mean-field model reproducing cerebellar physiological properties, which model-core is the transfer function transforming neurons spiking-patterns into time-continuous global activity. Combined with other models integrated in simulators, like DCM (Dynamic Causal Modeling) and TVB (The Virtual Brain), our cerebellar network will allow to investigate neuronal functions at the origin of macroscopic hemodynamic properties captured by BOLD.

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