activity and ln k on half of the runs (e.g., runs 1 and 3). Then a standard correlation between log k and %Now activation was calculated to determine if a relationship existed between mean activity and impulsivity. Group data from runs 1 and 3 were used to identify a voxel within each ROI for which the difficult > easy contrast estimates showed the largest negative correlation with ln k. Using the MarsBar toolbox within SPM5, a sphere with a radius of 6 mm was constructed around the peak voxel within each ROI. The second level analysis of the correlation examined the difficult > easy contrast on runs 2 and 4, and then used MarsBar to calculate the average contrast estimate within each sphere for each subject. Correlations were then computed between these activations and ln k. Results Of the 21 participants run in the magnet, useful data using reaction time were obtained for n = 12 and for the %Now analysis, n = 10. Data from the other two participants were not used because of a lack of variability. Data from the other participants were not used either because these individuals were classified as “shifters” before correction procedures were implemented (n = 6), provided inconsistent responses that did not yield useful data (n = 1), appeared to use a shortcut or rule (n = 1), or had too much head movement (n = 1). Table 1. Demographic Data
n = 12, African American (AA), Caucasian American (CA).
Our first goal was to validate the use of our DD task by demonstrating that more difficult trials did produce greater brain activation in executive function areas, as had been found previously. We found that many executive brain areas did show greater activation on difficult vs. easy trials (Table 2). We also found that reaction time and %Now were convergent measures of task difficulty, in that analyses with both measures showed that more difficult choices produced greater activation in executive function brain areas than easy choices (Table 2). Reaction times for control trials, which served as sensorimotor controls, were on average one second. Reaction times for actual trials ranged from 2-4 seconds across subjects, with harder decisions have longer reaction times. We found greater activation on difficult choices as defined by %Now in the inferior (Inf.) frontal gyrus (Fig. 3A), Lat. OFC (Fig. 3B), middle (Mid.) frontal gyrus (Fig. 3C), anterior cingulate gyrus (Fig. 3D), and the inferior and superior parietal lobules. We found greater activation on difficult choices as defined by longer reaction times in the inferior and middle frontal gyri and the Lat. OFC. Our other and main goal of the study was to show that level of impulsivity could predict executive system neural activation. Table 3 and Figures 4 and 5 shows brain areas that showed significantly less activation on difficult vs. easy trials, as defined by %Now and RT, associated with increasing impulsivity, presented as ln k, or a negative correlation (r). Higher k predicted less acti-
vation in the inferior and superior frontal gyri, anterior cingulate gyrus, and superior parietal lobule. Figure 3 (left). Activation on difficult > easy contrasts. (A) right inferior frontal gyrus, coronal view; (B) right lateral orbitofrontal cortex, axial view; (C) right middle frontal gyrus, coronal view; (D) left anterior cingulate cortex, sagittal view. Scale bar represents t-values. Discussion fMRI data collected to date from 12 obese women showed that our modified version of the delay-discounting of money task produced greater activation in executive function areas of the brain such as the inferior frontal gyrus and anterior cingulate cortex during difficult trials, compared to easier trials, mirroring the results of other comparable studies in normal or addicted individuals (Boettiger et al., 2007; Mcthe university of alabama at birmingham | inquiro • 89