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Chapter 7206this thesis, given that there was too little variation in happiness recognition performance. Yet, some evidence for the sensorimotor simulation account comes from findings linking stronger corrugator activity (%u201cfrowning%u201d) to higher accuracies in the recognition of negative expressions (Chapter 4 and Chapter 6, however not Chapter 5). The conditions under which sensorimotor (facial) simulations play a role in facial emotion recognition require future investigations. It should further be acknowledged that happy expressions were the only emotional expression of positive valence in our studies. Additionally, they are the most frequently encountered facial emotional expression in daily life (Calvo et al., 2014). High recognition accuracy could consequently also result from their distinctiveness within the task context as well as their high familiarity. While basic-emotion specific changes in autonomic nervous system activity are only sporadically described in Chapter 3 of the current thesis, this chapter highlights that physiological changes might specifically be evoked in response to more subtle and uncontrolled emotional cues, such as tears. Being genuine indicators of physiological arousal in the expressor (Kret, 2015) that are more difficult to control than muscle activity underlying emotional facial expressions, their resonance should also become particularly apparent in autonomic nervous system measures of the observer and might relate to their perception. Hence, future research should investigate the role of facial cues (e.g., dilated pupils, tears or a blush) more strongly in the context of the perception of basic emotions, but also of more complex emotions, such as blushing in the context of embarrassment or pride (Nikoli%u0107 et al., 2016, 2019; Riddell et al., 2023).As broadly outlined in the introduction, I believe interoception to be one relevant factor in explaining to which extent changes in one%u2019s own physiology link to interpretations of observed emotional expressions. The examination of this idea is, however, challenging, provided the complex nature of the multi-dimensional (e.g., accuracy vs. awareness) and multimodal (e.g., cardiovascular vs. respiratory) construct of interoception (Suksasilp & Garfinkel, 2022). Contrasting findings on shared variance between subjective and objective measures of interoceptive accuracy (Murphy et al., 2020), I did not observe that people who perceive themselves as more accurate in sensing their bodily signals (i.e., trait interoceptive accuracy) would actually be more accurate in judging whether their heartbeat is in sync with a series of tones or not (i.e., objective interoceptive accuracy; Chapter