Abstract #2662

Personalized fingerprint of neurodegenerative phenotypes using model-based simulations of brain networks

Anita Monteverdi¹, Fulvia Palesi², Michael Schirner^3,4,5,6,7, Francesca Argentino², Mariateresa Merante², Alberto Redolfi⁸, Francesca Conca⁹, Laura Mazzocchi¹⁰, Matteo Cotta Ramusino^2,11, Alfredo Costa^2,11, Anna Pichiecchio^2,10, Lisa Maria Farina⁹, Stefano Cappa^9,12, Viktor Jirsa¹³, Petra Ritter^3,4,5,6,7, Claudia A.M. Gandini Wheeler-Kingshott^1,2,14, and Egidio D’Angelo^1,2

¹Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy, ²Dept of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, ³Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany, ⁴Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Berlin, Germany, ⁵Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany, ⁶Einstein Center for Neuroscience Berlin, Berlin, Germany, ⁷Einstein Center Digital Future, Berlin, Germany, ⁸Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy, ⁹IRCCS Mondino Foundation, Pavia, Italy, ¹⁰Advanced Imaging and Radiomics Center, IRCCS Mondino Foundation, Pavia, Italy, ¹¹Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy, ¹²University Institute of Advanced Studies (IUSS), Pavia, Italy, ¹³Institut de Neurosciences des Systèmes, INSERM, INS, Aix Marseille University, Marseille, France, ¹⁴NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Department of Neuroinflammation, University College London, London, United Kingdom

Synopsis

Keywords: Alzheimer's Disease, Modelling, Frontotemporal DementiaThis work provides the first personalized and non-invasive assessment of resting-state networks connectivity and excitatory/inhibitory balance in health and in neurodegenerative diseases (Alzheimer’s disease, Frontotemporal Dementia). Multiple networks were characterized at single-subject level performing brain dynamics simulations with The Virtual Brain (TVB). TVB-derived parameters identified specific network properties (at single network and inter-network level) and their disruption in neurodegeneration, underlined the relationship between neurophysiology and neuropsychology, and outlined a personalized fingerprint sensitive to clinical severity. This model-based simulation of brain networks functional dynamics lay the groundwork for customized biomarkers research and defines new trajectories for designing novel tailored interventional workflows.

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