Dynamic models of large-scale whole brain network activity
How do large-scale brain dynamics arise from the anatomical structure of brains and support brain function and dysfunctions in movement, cognition, and perception? The necessary systematic explorations can only be performed in silico. Modeling large-scale brain activity with nonlinear dynamical systems theory allows the integration of experimental data from multiple modalities into a common framework that facilitates prediction, testing and possible refutation. The dynamic models rest on the complex spatial network architecture of brains that can be reconstructed from experimentally derived information about large-scale structural connectivity (white matter fiber tracts), that is, the connectome. This talk reviews the core assumptions that underlie this computational approach, the methodological framework that fosters the translation of theory into the laboratory, and into the clinic.