Statistics
Repeated measures ANOVA was used to investigate (1) within-subject treatment effects (psilocybin vs placebo) and (2) subgroup-by-treatment interaction effects of global and local graph metrics, mean DMN connectivity, local within-DMN strength, and sample entropy. The repeated measures ANOVA model was determined in MATLAB using fitrm and ranova functions. Outcome measures for graph metrics, DMN connectivity and entropy were calculated as the difference between TP2 (starting 18 min after drug application, 8.5 min duration) and TP1 (baseline before psilocybin or placebo administration, 8.5 min duration), respectively, and were then defined as the within-subject responses under the two different treatment conditions (psilocybin and saline) for each animal, while the subgroup was specified as the predictor variable (independent variable, ADE or control group).To control basic assumptions of the repeated measures ANOVA, Shapiro–Wilk [As the repeated measures ANOVA design only allows to assess the effects of ADE in a categorical approach, distinguishing dichotomously between control and ADE animals, we additionally integrated a dimensional analysis by correlating our fMRI metrics to the intensity of the ADE phenotype. For this analysis, we focused on the most prominent and best described FC phenotypes of psilocybin treatment, i.e., the psilocybin-induced decrease of DMN connectivity and the decrease of GBC. The ADE phenotype was quantified as the percentage alcohol consumption during relapse in comparison to baseline (normalized relapse rate). Then, Spearman’s rank correlations between normalized relapse rates and the decrease of mean DMN connectivity and within-DMN strength were calculated to assess for monotonic, but not necessarily linear associations to the relapse rate. For this analysis, the difference (ΔSal − ΔPsi) of the respective metric between saline and psilocybin treatment was used (metricFor detailed results from all our statistical analyses, see Supplementary Excel File “