Statistical analysis
We used the Statistical Parametric Mapping software (SPM, version 12) [For the first-level, we specified a general linear model (GLM) for each participant. We used a high-pass filter cutoff of 1/128 Hz to eliminate possible low-frequency confounds. Each regressor of interest was derived from the onsets of the stimuli and convoluted using a canonical hemodynamic response function (HRF) into the GLM to obtain weighted parameter estimates. The GLM consisted of eight regressors: (1) the onset of the trial, (2) the onset of the reception of a taste stimulus modulated by (3) the presence of the milkshake, (4) the trial-by-trial ratings of the perceived pleasantness, (5) the onset of the pleasantness question, (7) the onset of the intensity question, and (8) the onset of the familiarity question. We extracted the taste delivery contrast modulated by the perceived pleasantness for each participant for each session (43 participants × 2 sessions = 86).For the second-level, we entered the first level contrasts in a mixed measures 2 (session: pre or post) by 2 (treatment: placebo or liraglutide) ANOVA using the multivariate and repeated measures toolbox (MRM) [