Adaptive social behavior and mental well-being depend on not only recognizing emotional expressions but also, inferring the absence of emotion. While the neurobiology underwriting the perception of emotions is well studied, the mechanisms for detecting a lack of emotional content in social signals remain largely unknown. Here, using cutting-edge analyses of effective brain connectivity, we uncover the brain networks differentiating neutral and emotional body language. The data indicate greater activation of the right amygdala and midline cerebellar vermis to nonemotional as opposed to emotional body language. Most important, the effective connectivity between the amygdala and insula predicts people’s ability to recognize the absence of emotion. These conclusions extend substantially current concepts of emotion perception by suggesting engagement of limbic effective connectivity in recognizing the lack of emotion in body language reading. Furthermore, the outcome may advance the understanding of overly emotional interpretation of social signals in depression or schizophrenia by providing the missing link between body language reading and limbic pathways. The study thus opens an avenue for multidisciplinary research on social cognition and the underlying cerebrocerebellar networks, ranging from animal models to patients with neuropsychiatric conditions.

适应性的社会行为和心理健康不仅取决于识别情绪表达，而且还取决于推断出没有情绪。虽然对情感感知的神经生物学进行了深入研究，但在社会信号中检测情感内容不足的机制仍然未知。在这里，使用有效的大脑连通性的前沿分析，我们发现了区分中立和情感肢体语言的大脑网络。数据表明右杏仁核和中线小脑ver部更多地激活为非运动性，而不是情感性肢体语言。最重要的是，杏仁核和绝缘体之间的有效连通性可以预测人们识别情绪缺失的能力。这些结论通过建议肢体有效连接参与识别肢体语言阅读中的情感缺失，从而扩展了当前的情感感知概念。此外，通过提供肢体语言阅读和边缘途径之间的缺失联系，结果可能会促进对抑郁症或精神分裂症中社会信号过度情感解释的理解。因此，该研究为社会认知和潜在的小脑小脑网络的多学科研究开辟了道路，范围从动物模型到神经精神疾病患者。通过提供肢体语言阅读与边缘途径之间的缺失联系，结果可能会提高对抑郁症或精神分裂症中社会信号过度情绪化解释的理解。因此，该研究为社会认知和潜在的小脑小脑网络的多学科研究开辟了道路，范围从动物模型到神经精神疾病患者。通过提供肢体语言阅读与边缘途径之间的缺失联系，结果可能会促进对抑郁症或精神分裂症中社会信号过度情感解释的理解。因此，该研究为社会认知和潜在的小脑小脑网络的多学科研究开辟了道路，范围从动物模型到神经精神疾病患者。