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Embodied Facial Emotion Processing in Autism and Social Anxiety1796the German versions (Brand et al., 2023; T%u00fcnte et al., 2023) of the Interoceptive Accuracy Scale (IAS; Murphy et al., 2020), and the Interoceptive Attention Scale (IATS; Gabriele et al., 2022). The IAS evaluates subjective beliefs regarding one%u2019s capability to accurately perceive interoceptive signals, whereas the IATS assesses subjective beliefs concerning one%u2019s attention to interoceptive sensations. Participants judge internal body states of 21 bodily signals (e.g., heartbeat, pain, need to urinate) rated on a scale from 1 = strongly disagree to 5 = strongly agree, with scores ranging from 21-105. Higher scores indicate greater self-reported interoceptive accuracy or attention. With an alpha of .88 (95% CI [.84, .91]) and .89 (95% CI [.86, .92]), respectively, both the IAS and the IATS showed good internal consistency in our sample.Data AnalysisThe main interest of this study was to examine potential alterations in the link between physiological measures and facial emotion perception reports in autism and social anxiety. First, we conducted simple group comparisons on alterations in physiological responses and facial emotion perception reports on subjectlevel averaged data, as well as on alterations in interoception self-reports. Due to unequal sample sizes and variances in the three groups, we first ran a KruskalWallis test as omnibus test, which was followed by Wilcoxon rank sum tests (each clinical group against NC), using the Benjamini Hochberg correction for multiple comparisons. Prior to model fitting for the main analysis on a trial-bytrial level, self-reported Confidence in Emotion recognition accuracy and Perceived emotional intensity were standardized (i.e., centered and scaled) to facilitate model coefficient interpretation. As mimicry of different emotional facial expressions involves distinct muscle regions (see fEMG section), we fitted separate models to investigate alterations in the association between facial muscle responses and emotion perception of specific facial expressions. All negative expressions were included in the same models, together with the neutral expression, as they have all been linked to increased corrugator activity in past research. The variables Emotion category (anger, fear, sadness and neutral), Corrugator activity(baseline-corrected and z-scored), and Group (AS, SA, NC), as well as their twoway interactions (Emotion category*Group and Corrugator activity*Group) and the three-way interaction (Emotion category*Corrugator activity*Group), were thus predictors in (Generalized) Linear Mixed Models (GLMMS) with (1) Emotion recognition accuracy (binomial, 1 = correct/0 = incorrect), (2) Confidence in emotion