title: Empirical Bayes for Group (DCM) Studies: A Reproducibility Study.
abstract: This technical note addresses some key reproducibility issues in the dynamic causal modelling of group studies of event related potentials. Specifically, we address the reproducibility of Bayesian model comparison (and inferences about model parameters) from three important perspectives namely: (i) reproducibility with independent data (obtained by averaging over odd and even trials); (ii) reproducibility over formally distinct models (namely, classic ERP and canonical microcircuit or CMC models); and (iii) reproducibility over inversion schemes (inversion of the grand average and estimation of group effects using empirical Bayes). Our hope was to illustrate the degree of reproducibility one can expect from DCM when analysing different data, under different models with different analyses.
authors.affiliation: The Wellcome Trust Centre for Neuroimaging, University College London, Institute of Neurology London, UK.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Litvak
authors.affiliation: Queensland Brain Institute and Centre for Advanced Imaging, The University of Queensland Brisbane, QLD, Australia.
authors.forename: Marta
authors.initials: M
authors.lastname: Garrido
authors.affiliation: The Wellcome Trust Centre for Neuroimaging, University College London, Institute of Neurology London, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Zeidman
authors.affiliation: The Wellcome Trust Centre for Neuroimaging, University College London, Institute of Neurology London, UK.
authors.forename: Karl
authors.initials: K
authors.lastname: Friston
keywords: Bayesian model reduction; dynamic causal modelling; empirical Bayes; fixed effects; random effects; reproducibility