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The autonomic brain: Multi-dimensional generative hierarchical modelling of the autonomic connectome

Research output: Contribution to journalArticlepeer-review

James K Ruffle, Harpreet Hyare, Matthew A Howard, Adam D Farmer, A Vania Apkarian, Steven C R Williams, Qasim Aziz, Parashkev Nachev

Original languageEnglish
Pages (from-to)164-179
Number of pages16
JournalCortex
Volume143
DOIs
PublishedOct 2021

Bibliographical note

Funding Information: JR was supported by American Neurogastroenterology and Motility Society, the CDT i4health and the Issac Schapero research grant.PN is supported by the Wellcome Trust (213038/Z/18/Z) and the UCLH NIHR Biomedical Research Centre.HH is supported by the UCLH NIHR Biomedical Research Centre.SCRW and MAH are supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King's College London and the Medical Research Council (MR/N026969/1). Funding Information: PN is supported by the Wellcome Trust ( 213038/Z/18/Z ) and the UCLH NIHR Biomedical Research Centre . Funding Information: JR was supported by American Neurogastroenterology and Motility Society , the CDT i4health and the Issac Schapero research grant. Funding Information: SCRW and MAH are supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King’s College London and the Medical Research Council ( MR/N026969/1 ). Publisher Copyright: © 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors

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.

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