How to improve parameter estimates in GLM-based fMRI data analysis: cross-validated Bayesian model averaging

Abstract

In functional magnetic resonance imaging (fMRI), model quality of general linear models (GLMs) for first-level analysis is rarely assessed. In recent work (Soch et al., 2016: "How to avoid mismodelling in GLM-based fMRI data analysis: cross-validated Bayesian model selection", NeuroImage, vol. 141, pp. 469-489; http://dx.doi.org/10.1016/j.neuroimage.2016.07… (More)
DOI: 10.1016/j.neuroimage.2017.06.056

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