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Ten simple rules for dynamic causal modeling


Stephan, K E; Penny, W D; Moran, R J; den Ouden, H E M; Daunizeau, J; Friston, K J (2010). Ten simple rules for dynamic causal modeling. NeuroImage, 49(4):3099-3109.

Abstract

Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to conventional analysis techniques, a good knowledge of its theoretical foundations is needed to avoid pitfalls in its application and interpretation of results. By providing good practice recommendations for DCM, in the form of ten simple rules, we hope that this article serves as a helpful tutorial for the growing community of DCM users.

Abstract

Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to conventional analysis techniques, a good knowledge of its theoretical foundations is needed to avoid pitfalls in its application and interpretation of results. By providing good practice recommendations for DCM, in the form of ten simple rules, we hope that this article serves as a helpful tutorial for the growing community of DCM users.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > Neurochoice
08 University Research Priority Programs > Foundations of Human Social Behavior: Altruism and Egoism
Dewey Decimal Classification:570 Life sciences; biology
170 Ethics
330 Economics
Language:English
Date:15 February 2010
Deposited On:25 Mar 2010 13:29
Last Modified:23 Sep 2018 05:11
Publisher:Elsevier
ISSN:1053-8119
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.neuroimage.2009.11.015
PubMed ID:19914382

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