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Perceiving nonverbal behavior: Neural correlates of processing movement fluency and contingency in dyadic interactions

机译:感知非语言行为:二元互动中处理运动流畅性和偶然性的神经相关性

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Despite the fact that nonverbal dyadic social interactions are abundant in the environment, the neural mechanisms underlying their processing are not yet fully understood. Research in the field of social neuroscience has suggested that two neural networks appear to be involved in social understanding: (1) the action observation network (AON) and (2) the social neural network (SNN). The aim of this study was to determine the differential contributions of the AON and the SNN to the processing of nonverbal behavior as observed in dyadic social interactions. To this end, we used short computer animation sequences displaying dyadic social interactions between two virtual characters and systematically manipulated two key features of movement activity, which are known to influence the perception of meaning in nonverbal stimuli: (1) movement fluency and (2) contingency of movement patterns. A group of 21 male participants rated the "naturalness" of the observed scenes on a four-point scale while undergoing fMRI. Behavioral results showed that both fluency and contingency significantly influenced the "naturalness" experience of the presented animations. Neurally, the AON was preferentially engaged when processing contingent movement patterns, but did not discriminate between different degrees of movement fluency. In contrast, regions of the SNN were engaged more strongly when observing dyads with disturbed movement fluency. In conclusion, while the AON is involved in the general processing of contingent social actions, irrespective of their kinematic properties, the SNN is preferentially recruited when atypical kinematic properties prompt inferences about the agents' intentions.
机译:尽管在环境中非语言二元社会互动非常丰富,但其处理背后的神经机制尚未得到充分理解。社会神经科学领域的研究表明,两个神经网络似乎参与了社会理解:(1)行为观察网络(AON)和(2)社会神经网络(SNN)。这项研究的目的是确定二元社会互动中观察到的AON和SNN对非语言行为处理的不同贡献。为此,我们使用了简短的计算机动画序列来显示两个虚拟角色之间的二元社会互动,并系统地操纵了运动活动的两个关键特征,这些特征会影响非语言刺激中的意义感知:(1)运动流畅性和(2)运动方式的偶然性。一组21位男性参与者在进行fMRI时以四点量表对观察到的场景的“自然度”进行了评分。行为结果表明,流畅性和偶然性都显着影响了所呈现动画的“自然”体验。通常,在处理偶然的​​运动模式时优先选择AON,但不会区分不同程度的运动流畅性。相反,当观察运动流畅度受到干扰的二分体时,SNN的区域参与度更高。总之,尽管AON参与了偶然性社会行为的一般处理,无论其运动学特性如何,当非典型运动学特性提示对代理人意图的推断时,优先选择SNN。

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