Dynamic causal modeling for EEG and MEG

Kiebel, Stefan J., Garrido, Marta I., Moran, Rosalyn, Chen, Chun-Chuan and Friston, Karl J. (2009) Dynamic causal modeling for EEG and MEG. Human Brain Mapping, 30 6: 1866-1876. doi:10.1002/hbm.20775

Author Kiebel, Stefan J.
Garrido, Marta I.
Moran, Rosalyn
Chen, Chun-Chuan
Friston, Karl J.
Title Dynamic causal modeling for EEG and MEG
Journal name Human Brain Mapping   Check publisher's open access policy
ISSN 1065-9471
Publication date 2009-06
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1002/hbm.20775
Open Access Status
Volume 30
Issue 6
Start page 1866
End page 1876
Total pages 11
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Abstract We present a review of dynamic causal modeling (DCM) for magneto- and electroencephalography (M/EEG) data. DCM is based on a spatiotemporal model, where the temporal component is formulated in terms of neurobiologically plausible dynamics. Following an intuitive description of the model, we discuss six recent studies, which use DCM to analyze M/EEG and local field potentials. These studies illustrate how DCM can be used to analyze evoked responses (average response in time), induced responses (average response in time-frequency), and steady-state responses (average response in frequency). Bayesian model comparison plays a critical role in these analyses, by allowing one to compare equally plausible models in terms of their model evidence. This approach might be very useful in M/EEG research; where correlations among spatial and neuronal model parameter estimates can cause uncertainty about which model best explains the data. Bayesian model comparison resolves these uncertainties in a principled and formal way. We suggest that DCM and Bayesian model comparison provides a useful way to test hypotheses about distributed processing in the brain, using electromagnetic data.
Keyword EEG
Network model
Bayesian analysis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collection: Queensland Brain Institute Publications
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