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Understanding DCM: ten simple rules for the clinician.

Kahan, J; Foltynie, T; (2013) Understanding DCM: ten simple rules for the clinician. Neuroimage , 83 542 - 549. 10.1016/j.neuroimage.2013.07.008. Green open access

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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.

Type: Article
Title: Understanding DCM: ten simple rules for the clinician.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2013.07.008
Publisher version: http://dx.doi.org/10.1016/j.neuroimage.2013.07.008
Language: English
Additional information: © 2013 Elsevier Inc. Open Access under CC BY licence
Keywords: Action Potentials, Algorithms, Animals, Brain, Brain Mapping, Computer Simulation, Humans, Models, Neurological, Nerve Net, Terminology as Topic
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
URI: https://discovery.ucl.ac.uk/id/eprint/1400919
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