The autonomic brain: Multi-dimensional generative hierarchical modelling of the autonomic connectome
James K. Ruffle, Harpreet Hyare, Matthew A. Howard, Adam D. Farmer, A. Vania Apkarian, Steven Williams, Qasim Aziz, Parashkev Nachev
Abstract
The autonomic nervous system governs the body's multifaceted internal adaptation to diverse changes in the external environment, a role more complex than is accessible to the methods-and data scales-hitherto used to illuminate its operation. Here we apply generative graphical modelling to large-scale multimodal neuroimaging data encompassing normal and abnormal states to derive a comprehensive hierarchical representation of the autonomic brain. We demonstrate that whereas conventional structural and functional maps identify regions jointly modulated by parasympathetic and sympathetic systems, only graphical analysis discriminates between them, revealing the cardinal roles of the autonomic system to be mediated by high-level distributed interactions. We provide a novel representation of the autonomic system-a multidimensional, generative network-that renders its richness tractable within future models of its function in health and disease.