Our main goal was to identify associations (linear and quadratic) of BMI and characteristics of eating behavior (CR, DIS) with BOLD activation during volitional regulation of food craving. We tested separate regression models to individually assess the relationship of BMI, CR, DIS or regulation success and the respective regulation contrasts (REGULATE_TASTY>ADMIT_TASTY, REGULATE_TASTY>REGULATE_NOT_TASTY) including age (analyses of BMI, CR, DIS, regulation success) or age and BMI (analysis of BMI 2 ) as covariates. To assess the relationship of craving intensity and appetitive brain activity, separate regression models were tested on the respective craving contrasts (ADMIT_TASTY>REGULATE_TASTY, ADMIT_TASTY>ADMIT_NOT_TASTY). Please see Supplementary Table III for a summary of performed regression analyses. Second-level maps were thresholded voxelwise at P<0.001 and corrected for multiple comparisons at a cluster threshold of P<0.05 (family-wise error) for the whole brain.
Useful associations investigation
Functional connectivity was assessed by means of psychophysiological interaction (PPI) analysis. 28 Source regions were based on the above-mentioned regression analysis of BOLD activation and BMI, our primary research focus. Individual BOLD signal time series within 4-mm spheres surrounding detected peak coordinates were extracted (based on the inverted U-shaped relationship of BMI and REGULATE_TASTY>ADMIT_TASTY, please see ‘Overall performance’ section and Table 2 for details). General linear models were estimated separately for every source region including the following regressors: Time course of the respective source region (physiological vector), a vector coding for the main effect (psychological vector; REGULATE_TASTY>ADMIT_TASTY; with the former term weighted as +1 and the latter one weighted as ?1), and the PPI term (element-by-element product between the time course of the source region and the vector coding the main effect). The models also included realignment parameters as nuisance regressors. Single-subject contrasts for the PPI regressors were calculated. In the second-level analysis, we aimed to identify regions whose functional connectivity was related to BMI (linear and quadratic) or characteristics of eating behavior (CR, DIS). Therefore, the PPI terms were regressed on these measures in separate multiple regression analyses. Second-level models also included the regressors of no interest mentioned under subsection ‘Analysis of BOLD response’. Second-level maps were thresholded voxelwise at P<0.001 and corrected for multiple comparisons at a cluster threshold of P<0.05 (family-wise error) for the whole brain. Clusters were considered to be significant at P<0.017 (Bonferroni adjustment to account for the number of investigated seeds). Please see Supplementary Table III for a summary of performed regression analyses.
Results
I seen a robust confident correlation from Bmi and you can DIS (Roentgen 2 =0.285, P>0.001, Pearson correlation, Second Contour Ia). Numerous regression study shown a negative relationship out of Bmi dos that have CR (Roentgen dos =0.151, P=0.038, covariate Bmi; Additional Figure Ib), indicating an ugly You-molded relationship. Desire power did not associate having Body mass index (R=?0.206, P=0.185, Pearson relationship). We located a trend away from an awful relationship anywhere between controls profits and you can Bmi (R=?0.295, P=0.055, Pearson relationship). Look for Desk 1 for detailed statistics.
Tips
To control their desire, all people (specifically over weight volunteers) imagined the new bad enough time-identity consequences regarding restaurants the brand new represented palatable dining. Extremely users transformed anywhere between more controls strategies throughout the experiment (get a hold of Additional Desk IV to possess information on method fool around with). When instructed to accept, all of the professionals thought liking otherwise feel of one’s showed ingredients.
Matchmaking between Challenging pastime and you can Body mass index, food behavior, desire power otherwise personal control profits
Activity in a cluster comprising left putamen, amygdala and girl looking for sugar daddy Midlothian Illinois insula was nonlinearly (inverted U-shaped) related to BMI during volitional regulation devoid of craving influences (REGULATE_TASTY>ADMIT_TASTY; Table 2, Figure 2). Activation during regulation specific to hedonic food (REGULATE_TASTY>REGULATE_NOT_TASTY) was unrelated to BMI. We found no linear relationships with BMI. Craving intensity correlated positively with activity in the right hippocampus/amygdala during craving devoid of volitional regulatory influences (ADMIT_TASTY>REGULATE_TASTY; Table 2, Supplementary Figure X), but did not correlate with activation during craving specific to hedonic food (ADMIT_TASTY>ADMIT_NOT_TASTY). Neither subjective regulation success nor measures of eating behavior were significantly related to task-related BOLD activity. The above-mentioned results indicate some lateralization of the findings. However, when a less strict threshold was applied, bilateral BOLD activation of all mentioned regions associated with BMI and craving intensity was observed (relationship of BOLD and BMI: t-values thresholded at P<0.05, uncorrected; relationship of BOLD and craving intensity: t-values thresholded at P<0.001, uncorrected).