منابع مشابه
Bayesian model selection for group studies
Bayesian model selection (BMS) is a powerful method for determining the most likely among a set of competing hypotheses about the mechanisms that generated observed data. BMS has recently found widespread application in neuroimaging, particularly in the context of dynamic causal modelling (DCM). However, so far, combining BMS results from several subjects has relied on simple (fixed effects) me...
متن کاملBayesian model selection for group studies - Revisited
In this paper, we revisit the problem of Bayesian model selection (BMS) at the group level. We originally addressed this issue in Stephan et al. (2009), where models are treated as random effects that could differ between subjects, with an unknown population distribution. Here, we extend this work, by (i) introducing the Bayesian omnibus risk (BOR) as a measure of the statistical risk incurred ...
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This technical note describes the construction of posterior probability maps (PPMs) for Bayesian model selection (BMS) at the group level. This technique allows neuroimagers to make inferences about regionally specific effects using imaging data from a group of subjects. These effects are characterised using Bayesian model comparisons that are analogous to the F-tests used in statistical parame...
متن کاملCorrigendum to "Bayesian model selection for group studies" [NeuroImage 46 (2009) 1005-1017]
Corrigendum to “Bayesian model selection for group studies” [NeuroImage 46 (2009) 1005–1017] Klaas Enno Stephan ⁎, Will D. Penny , Jean Daunizeau , Rosalyn J. Moran , Karl J. Friston a a Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3BG, UK b Laboratory for Social and Neural Systems Research, Institute for Empirical Rese...
متن کاملAnatomically Informed Bayesian Model Selection for fMRI Group Data Analysis
A new approach for fMRI group data analysis is introduced to overcome the limitations of standard voxel-based testing methods, such as Statistical Parametric Mapping (SPM). Using a Bayesian model selection framework, the functional network associated with a certain cognitive task is selected according to the posterior probabilities of mean region activations, given a pre-defined anatomical parc...
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ژورنال
عنوان ژورنال: NeuroImage
سال: 2009
ISSN: 1053-8119
DOI: 10.1016/j.neuroimage.2009.03.025