Page 230 - Like me, or else... - Michelle Achterberg

Chapter 8
available money on the next trial was increased (decreasing adjustment algorithm) (Du et al., 2002).
The amount of immediately available money the participant considered to be equivalent to the €10 delayed reward was taken to indicate the subjective value of the delayed rewards. Based on these so called ‘indifference points’, the area under the discounting curve (AUC) was obtained, an often-used measure of amount of discounting (Myerson et al., 2001). The normalized AUC ranges from 0 (complete discounting) to 1 (no discounting). The smaller the AUC, the faster people discount the delayed reward and the more impulsive (or delay aversive) they are. The task was presented as a hypothetical delay-discounting task. However, several studies have shown that choices on a hypothetical delay- discounting task substantially and significantly correlate (r’s up to 0.74) with choices on a delay discounting task with real rewards in adults (Bickel et al., 2009; Scheres et al., 2010).
Imaging acquisition and processing
The same imaging acquisition was used as described in Peper et al. (2013). Scans were acquired on a 3-Tesla Philips Achieva MRI system. Two transverse Diffusion Weighted Imaging (DWI) scans were obtained with the following parameter settings: 30 diffusion-weighted volumes with different noncollinear diffusion directions with b-factor 1,000 s/mm2 and 5 diffusion-unweighted volumes (b- factor 0 s/mm2); anterior -posterior phase encoding direction; parallel imaging SENSE factor = 3; flip angle = 90 degrees; 75 slices of 2 mm; no slice gap; reconstruction matrix 128 × 128; Field of view (FOV) = 240 × 240 mm; TE = 69 ms; TR = 7,315 ms; total scan duration = 271 s per DWI set. The second DWI set had identical parameter settings as used for the first set except that it was acquired with a reversed k-space readout direction (posterior-anterior phase encoding direction) enabling the removal of susceptibility artifacts during post processing (Andersson et al., 2003). During scanning, the FOV was angulated according to the anterior commissure-posterior commissure line, and diffusion gradients were adjusted accordingly during data processing. Subsequently, diffusion scans were realigned to the averaged b0 scan and corrected for motion, eddy current, and susceptibility distortions (Andersson and Skare, 2002; Andersson et al., 2003). A tensor was fitted to the diffusion profile in each voxel using a robust tensor fitting method to correct for possible effects of cardiac pulsation and head motion (Chang et al., 2005; Chang et al., 2012). The main diffusion direction was determined as the principal eigenvector of the eigenvalue decomposition of this fitted tensor.
Based on the eigenvalue decomposition, two measures derived from the diffusion tensor were computed: 1) the fractional anisotropy (FA), which measures the directional variation of diffusion and ranges from 0 (no preferred diffusion direction) and 1 (highly preferred diffusion direction) and 2) mean
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