Statistical analyses
REGRESSION
To test whether the drug manipulation was successful, blood pressure and heart rate measurements as well as eye-tracking data were analyzed using mixed-effect ANOVAs with the between-subjects factor group and the within-subject factor time. Post-hoc t-tests were used to follow-up on group differences in these measures. A mixed-effects logistic regression analysis was used to explain choice behavior. Choice was coded as stay vs. switch, indicated by 0 and 1, respectively. It was explained as a function of previous return (number of apples obtained from the previous harvest), travel time (short = 0 vs. long = 1), depletion rate, number of previous stays at current tree, and group (placebo vs. amisulpride vs. propranolol) with the placebo group as reference. We used the Akaike Information Criterion (AIC) [In a next step, we tested whether the factors’ estimates changed over time and whether this was different in the experimental groups. Therefore, we fitted our model separately for the first half of the task (blocks 1 and 2) and the second half (blocks 3 and 4). Note that a blockwise comparison cannot be applied here, since the blocks had either an environment with short or long travel time and these blocks were alternating. Whether the first block contained a short or long travel time orchard was counterbalanced so that an analysis based on continuous blocks would compare choices at short travel times to behavior at long travel times.To further quantify task performance, we tested whether the total sum of rewards obtained throughout the task and the proportion of switch choices differed between the experimental groups in ANOVAs with the between factor group. In a next step, we tested whether the task performance measures differed in environments with short versus long travel times in mixed-effect ANOVAs with the between-subjects factor group and the within-subject factor travel time. All analyses were performed in R [