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  A dynamic causal model for evoked and induced responses

Chen, C.-C., Kiebel, S. J., Kilner, J. M., Ward, N. S., Stephan, K. E., Wang, W.-J., et al. (2012). A dynamic causal model for evoked and induced responses. NeuroImage, 59(1), 340-348. doi:10.1016/j.neuroimage.2011.07.066.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0012-14B7-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-CE1D-6
Genre: Journal Article

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 Creators:
Chen, Chun-Chuan1, 2, Author
Kiebel, Stefan J.1, 3, Author              
Kilner, James M.1, Author
Ward, Nick S.4, Author
Stephan, Klaas E.1, 5, Author
Wang, Wei-Jen6, Author
Friston, Karl J.1, Author
Affiliations:
1Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
2Graduate Institute of Biomedical Engineering, National Central University, Jhongli, Taiwan, ou_persistent22              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
4Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, United Kingdom, ou_persistent22              
5Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Switzerland, ou_persistent22              
6Department of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan, ou_persistent22              

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 Abstract: Neuronal responses exhibit two stimulus or task-related components: evoked and induced. The functional role of induced responses has been ascribed to 'top-down' modulation through backward connections and lateral interactions; as opposed to the bottom-up driving processes that may predominate in evoked components. The implication is that evoked and induced components may reflect different neuronal processes. The conventional way of separating evoked and induced responses assumes that they can be decomposed linearly; in that induced responses are the average of the power minus the power of the average (the evoked component). However, this decomposition may not hold if both components are generated by nonlinear processes. In this work, we propose a Dynamic Causal Model that models evoked and induced responses at the same time. This allows us to explain both components in terms of shared mechanisms (coupling) and changes in coupling that are necessary to explain any induced components. To establish the face validity of our approach, we used Bayesian Model Selection to show that the scheme can disambiguate between models of synthetic data that did and did not contain induced components. We then repeated the analysis using MEG data during a hand grip task to ask whether induced responses in motor control circuits are mediated by 'top-down' or backward connections. Our result provides empirical evidence that induced responses are more likely to reflect backward message passing in the brain, while evoked and induced components share certain characteristics and mechanisms.

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Language(s): eng - English
 Dates: 2011-07-222011-07-302012-01-02
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2011.07.066
PMID: 21835251
PMC: PMC3202632
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 (1) Sequence Number: - Start / End Page: 340 - 348 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166