Task‐based fMRI
HED
In whole‐brain analysis at the first level, explanatory variables were entered into a general linear model in FSL's fMRI Expert Analysis Tool (FEAT) for the three image categories (LED, HED and non‐food cues) with a separate model run for each scan session per participant. Three contrasts were defined to examine responses to food cues minus non‐food objects ([i] food [HED + LED] > non‐food cues; [ii] HED > non‐food cues; and [iii] LED > non‐food cues) and a further two contrasts were defined to compare responses between high‐ and low‐value foods ([iv] HED > LED; and [v] LED > HED). The first three volumes (5.4 s) of the functional data were discarded to account for saturation effects. Clusters of activation were identified after thresholding the z‐statistic images at z > 3.1 using a corrected cluster significance threshold of The contrasts of parameter estimates generated at the first level were used to conduct higher‐level group analysis on the five contrasts in four stages:a a the a Analysis was performed both with and without adjustment for CBF by adding the appropriate CBF map as a voxelwise (confound) explanatory variable in the higher‐level FEAT model. Information on the peak value of activated clusters was obtained using the atlasquery tool in FSL (and the associated autoaq script), specifying the Harvard–Oxford cortical and subcortical atlases. The FSL tool FEATquery was used to extract the percentage change in BOLD signal for the peak of each activated cluster.