title: Understanding DCM: ten simple rules for the clinician.
abstract: Despite almost a decade since the introduction of Dynamic Causal Modelling (DCM), there remains some confusion within the wider neuroimaging, neuroscience and clinical communities as to what DCM studies are probing, and what all the jargon means. We provide ten simple rules, and a theoretical example to gently introduce the reader to the rationale behind DCM analyses, and how one should consider neuroimaging data and experiments that use DCM. It is deliberately written as a primer or orientation for non-technical imaging neuroscientists or clinicians who have had to contend with the technical intricacies of understanding DCM.
authors.affiliation: Sobell Department for Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, UK. Electronic address: joshua.kahan@ucl.ac.uk.
authors.forename: Joshua
authors.initials: J
authors.lastname: Kahan
authors.forename: Tom
authors.initials: T
authors.lastname: Foltynie
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009626:Terminology as Topic