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Empirical Bayes for Group (DCM) Studies: A Reproducibility Study

Litvak, V; Garrido, M; Zeidman, P; Friston, K; (2015) Empirical Bayes for Group (DCM) Studies: A Reproducibility Study. Frontiers in Human Neuroscience , 9 , Article 670. 10.3389/fnhum.2015.00670. Green open access

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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.

Type: Article
Title: Empirical Bayes for Group (DCM) Studies: A Reproducibility Study
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fnhum.2015.00670
Publisher version: http://doi.org/10.3389/fnhum.2015.00670
Language: English
Additional information: © 2015 Litvak, Garrido, Zeidman and Friston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: Science & Technology, Social Sciences, Life Sciences & Biomedicine, Neurosciences, Psychology, Neurosciences & Neurology, empirical Bayes, random effects, fixed effects, dynamic causal modelling, Bayesian model reduction, reproducibility, EVOKED-RESPONSES, MODEL, CONNECTIONS, INVERSION, SELECTION, FMRI, MEG, EEG
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/1483737
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