Silvia Maria Marchese1, Fulvia Palesi2,3, Mariagrazia Bruzzone4, Anna Nigri4, Stefano D'Arrigo5, Chiara Pantaleoni5, Claudia AM Gandini Wheeler-Kingshott2,3,6, Egidio D'Angelo2,3, and Paolo Cavallari1
1Human Physiology Section of the DePT, Università degli Studi di Milano, Milano, Italy, 2Department of Brain and Behavioral Science, Università degli Studi di Pavia, Pavia, Italy, 3Brain Connectivity Center Research Department, IRCCS Mondino Foundation, Pavia, Italy, 4Neuroradiology Department, Fondazione IRCCS Istituto Neurologico "C. Besta", Milano, Italy, 5Developmental Neurology Department, Fondazione IRCCS Istituto Neurologico "C. Besta", Milano, Italy, 6Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, NMR Research Unit, Queen Square MS Centre, London, United Kingdom
1Human Physiology Section of the DePT, Università degli Studi di Milano, Milano, Italy, 2Department of Brain and Behavioral Science, Università degli Studi di Pavia, Pavia, Italy, 3Brain Connectivity Center Research Department, IRCCS Mondino Foundation, Pavia, Italy, 4Neuroradiology Department, Fondazione IRCCS Istituto Neurologico "C. Besta", Milano, Italy, 5Developmental Neurology Department, Fondazione IRCCS Istituto Neurologico "C. Besta", Milano, Italy, 6Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, NMR Research Unit, Queen Square MS Centre, London, United Kingdom
Brain dynamics simulated in a subject with Joubert syndrome highlighted the impact of excluding cerebellum from brain network in cerebellar dysfunction. Pearson correlation coefficient is strongly decreased when cerebro-cerebellar connectivity is excluded from the simulation.
Table 1: Parameters forwhole-brain network, cerebral subnetwork and embedded cerebro-cerebellar subnetwork.Optimal value for global coupling (Gcoupl) and Pearson correlation coefficients (PCC) between structural connectivity (SC), experimental (expFC) and simulated functional connectivity (simFC) are reported.
Figure 1: A) Experimental matrices of structural connectivity (expSC) and functional connectivity (expFC) in the patient with Joubert syndrome. B) Simulated functional connectivity (simFC) matrices for whole-brain network (left), cerebral subnetwork (center) and embedded cerebro-cerebellar subnetwork (right). In each matrix, rows and columns represent a specific brain region (node), while each intersection point represents a connection, weighted by the number of streamlines, between two nodes (edge).