*2.4. Statistical Analysis*

With reference to the ROI method, data were analyzed using JASP version 0.16 [19]. We used multiple linear regression analysis to compare the regional *k*icer values between ASD and controls and to assess the associations of *k*icer with the AQ total and subscale scores. We adjusted for four confounders: age, sex, smoker status (yes/no), and scanner type (Vereos/Biograph Horizon). A two-tailed *p*-value of 0.05 was used to evaluate the statistical significance. In addition, Bayesian analyses were conducted (see Supplementary Methods S2). Voxel-based comparisons were made in SPM12. An independent samples *t*-test was used to examine group differences in *k*icer, and multiple linear regression analysis was used to examine associations between *k*icer and AQ scores. Confounders included age, sex, smoker status, and scanner type. A family-wise error (FWE) rate of α = 0.05 was used to evaluate the statistical significance. We conducted several additional control analyses to assess the robustness of the findings. First, we repeated our analyses restricting ourselves to voxels with *k*icer values above 0.001 and 0.005, effectively excluding voxels showing little specific [18F]-FDOPA uptake. Second, we repeated our analyses with unsmoothed data and after smoothing with a 4 mm FWHM Gaussian filter (i.e., instead of the 8 mm FWHM Gaussian filter that we used for the main analysis). Third, we conducted the analyses for the two PET/CT scanners separately.
