Contributed by fbeyer on Jan. 12, 2017
Description: ICA analysis was applied to identify spatially independent components using the GIFT toolbox. Then multivariate model selection was performed using the MANCOVA-toolbox with age, sex, body mass index registration quality and mean framewise displacement as inputs. For the default mode network component 29 sex, BMI and registration quality were found to be significant predictors and thus entered into univariate analysis within the default mode network. Here we present the result for the BMI contrast as raw p-values.Task View 3D View
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