Page 232 - Like me, or else... - Michelle Achterberg

Chapter 8
callosum (manually delineated on the midsagittal slice), the uncinate fasciculus, and the longitudinal fascicules (manually delineated by a plane through the temporal lobes where the amygdala was located). For fiber selection, all ROIs had to be defined only once, on the model brain. For an individual example of fronto- striatal fiber tracts, see Figure 1. All voxels within the selected fronto-striatal tracts were flagged, resulting in individual binary maps of fronto-striatal tracts (in model space) for each participant of the sample on both time-points T1 and T2. Subsequently, the VOI was created for fronto-striatal tracts of the sample: Every voxel within the fronto-striatal tract should have a fiber running through in at least 50% of the sample (i.e. thresholded at 50%; Figure 1). Then this particular voxel was flagged and added to the VOI. The left and right hemisphere were combined to ensure comparability with earlier reports (Liston et al., 2006; de Zeeuw et al., 2012; Peper et al., 2013; van den Bos et al., 2015) that did not report hemispheric differences in relation to impulsive behavior. Within the VOI of the fronto-striatal tract, DTI metrics (FA and MD) were calculated for each individual subject of the whole sample.
Global white matter
As a control measure of global white matter development and to test for specificity of the contribution of fronto-striatal white matter tracts to delay discounting behavior, white matter tracts of the whole brain –excluding fronto- striatal tracts- were examined as well.
Statistical analyses
Statistical analyses were conducted with Statistical Package for Social Sciences (SPSS), version 21 and in R, version 3.1.1. The contribution of gender and intelligence to delay of gratification skills (AUC normalized) were explored using independent sample T-tests and Pearson’s correlation in SPSS. Pearson’s correlation in SPSS were also used to investigate the stability of delay of gratification skills (AUC normalized) and white matter integrity (FA and MD) over time. Furthermore, mediation analyses were performed to test whether the relation between age and delay discounting was mediated by fronto-striatal white matter integrity, measured by FA and MD. For correct comparison between FA and MD we used z-values in the mediation analyses. The present study used a bootstrapping approach to mediation as implemented in the SPSS macros of Preacher and Hayes (Preacher and Hayes, 2008). Confidence intervals (95%) were estimated using the bias-corrected bootstrap method (number of resamples = 10000) implemented in the macros.
Mixed models were used to investigate age-related change (linear, quadratic or cubic) in delay of gratification skills (AUC normalized) and fronto- striatal white matter integrity (FA and MD). Analyses were performed with the nlme package in R (Pinheiro et al., 2013). Mixed models are particularly useful in
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