Publication: Bayesian model reduction and empirical Bayes for group (DCM) studies
Bayesian model reduction and empirical Bayes for group (DCM) studies
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Friston, K. J., Litvak, V., Oswal, A., Razi, A., Stephan, K. E., van Wijk, B. C. M., Ziegler, G., & Zeidman, P. (2016). Bayesian model reduction and empirical Bayes for group (DCM) studies. NeuroImage, 128, 413–431. https://doi.org/10.1016/j.neuroimage.2015.11.015
Abstract
Abstract
Abstract
This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences
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Creators (Authors)
- Friston, K J
- Litvak, V
- Oswal, A
- Razi, Adeel
- Stephan, K E
- van Wijk, B C M
- Ziegler, G
- Zeidman, Peter
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Citations
Friston, K. J., Litvak, V., Oswal, A., Razi, A., Stephan, K. E., van Wijk, B. C. M., Ziegler, G., & Zeidman, P. (2016). Bayesian model reduction and empirical Bayes for group (DCM) studies. NeuroImage, 128, 413–431. https://doi.org/10.1016/j.neuroimage.2015.11.015
