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  Critical comments on dynamic causal modelling

Lohmann, G., Erfurth, K., Mueller, K., & Turner, R. (2012). Critical comments on dynamic causal modelling. NeuroImage, 59(3), 2322-2329. doi:10.1016/j.neuroimage.2011.09.025.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0012-2919-F Version Permalink: http://hdl.handle.net/21.11116/0000-0003-CF9E-3
Genre: Journal Article

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Lohmann_2012_Critical.pdf (Publisher version), 700KB
 
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 Creators:
Lohmann, Gabriele1, Author              
Erfurth, Kerstin2, Author
Mueller, Karsten3, Author              
Turner, Robert1, Author              
Affiliations:
1Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
2University of Applied Sciences, Leipzig, Germany, ou_persistent22              
3Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              

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Free keywords: Dynamic causal modelling; Model validation; Combinatorial explosion
 Abstract: Dynamic causal modelling (DCM) (Friston et al., 2003) is a technique designed to investigate the influence between brain areas using time series data obtained by EEG/MEG or functional magnetic resonance imaging (fMRI). The basic idea is to fit various models to time series data, and select one of those models using Bayesian model comparison. Here, we present a critical evaluation of DCM in which we show that DCM can be challenged on several grounds. We will discuss three main points relating to combinatorial explosion, the validity of the model selection procedure, and problems with respect to model validation.

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Language(s): eng - English
 Dates: 2011-09-142011-09-212012-02-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2011.09.025
PMID: 22001162
Other: Epub 2011
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 59 (3) Sequence Number: - Start / End Page: 2322 - 2329 Identifier: ISSN: 1053-8119
CoNE: /journals/resource/954922650166