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.
Preview |
Text
Litvak_Empirical Bayes for Group (DCM) Studies%3A A Reproducibility Study.pdf - Published Version Download (2MB) | Preview |
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 |
Archive Staff Only
View Item |