From genes to network models of Alzheimer's disease: Biological framework for multi-scale brain simulation with The Virtual Brain Leon Stefanovski1*, Jil Mona Meier1, Roopa Kalsank Pai1,2, Paul Triebkorn1,3, Tristram Lett1, Leon Martin1, Konstantin Bülau1, Martin Hofmann-Apitius4, Ana Solodkin5, Anthony Randal MCIntosh6, Petra Ritter1,2,* 1 Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt- Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Brain Simulation Section, Berlin, Germany 2 Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany 3 Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France 4 Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany 5 Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States 6 Baycrest Health Sciences, Rotman Research Institute, Toronto, Ontario, Canada * CorrespondenCe: Leon Stefanovski
[email protected] Petra Ritter
[email protected] Keywords: Alzheimer’s Disease, The Virtual Brain, Brain Simulation, Multi-sCale Brain Modeling, ConneCtomiCs ABSTRACT While the knowledge in neuroscience and the possibilities in clinical neurology have improved for many years, neurogenerative diseases and associated dementia remain a growing problem. Alzheimer’s Disease (AD) is the most common cause of dementia and also represents the most prevalent type of neurodegenerative diseases. For AD, disease-modifying treatments are presently lacking and the understanding of disease mechanisms remain incomplete. In the present review, we consider candidate contributing factors leading to AD and we evaluate novel computational brain simulation methods to further disentangle their potential roles. We first discuss existing computational models of AD that aim to provide a mechanistic understanding of the disease.