Department of Cognitive Science, Johns Hopkins University, MD 21218, United States.
Department of Cognitive Science, Johns Hopkins University, MD 21218, United States.
Neuroimage. 2021 Dec 15;245:118741. doi: 10.1016/j.neuroimage.2021.118741. Epub 2021 Nov 17.
Recognizing others' social interactions is a crucial human ability. Using simple stimuli, previous studies have shown that social interactions are selectively processed in the superior temporal sulcus (STS), but prior work with movies has suggested that social interactions are processed in the medial prefrontal cortex (mPFC), part of the theory of mind network. It remains unknown to what extent social interaction selectivity is observed in real world stimuli when controlling for other covarying perceptual and social information, such as faces, voices, and theory of mind. The current study utilizes a functional magnetic resonance imaging (fMRI) movie paradigm and advanced machine learning methods to uncover the brain mechanisms uniquely underlying naturalistic social interaction perception. We analyzed two publicly available fMRI datasets, collected while both male and female human participants (n = 17 and 18) watched two different commercial movies in the MRI scanner. By performing voxel-wise encoding and variance partitioning analyses, we found that broad social-affective features predict neural responses in social brain regions, including the STS and mPFC. However, only the STS showed robust and unique selectivity specifically to social interactions, independent from other covarying features. This selectivity was observed across two separate fMRI datasets. These findings suggest that naturalistic social interaction perception recruits dedicated neural circuity in the STS, separate from the theory of mind network, and is a critical dimension of human social understanding.
识别他人的社交互动是人类的一项重要能力。先前的研究使用简单的刺激表明,社交互动会被选择性地处理在颞上沟(STS)中,但使用电影的先前研究表明,社交互动会被处理在大脑的内侧前额叶皮层(mPFC)中,这是心理理论网络的一部分。当控制其他相关的感知和社交信息(如面孔、声音和心理理论)时,在真实世界的刺激中观察到社交互动的选择性程度仍然未知。本研究利用功能磁共振成像(fMRI)电影范式和先进的机器学习方法,揭示了自然社交互动感知背后的大脑机制。我们分析了两个公开的 fMRI 数据集,这些数据集是在 MRI 扫描仪中收集的,参与者包括男性和女性(n=17 和 18),观看了两部不同的商业电影。通过执行体素编码和方差分割分析,我们发现广泛的社会情感特征可以预测社会大脑区域的神经反应,包括 STS 和 mPFC。然而,只有 STS 显示出对社交互动的稳健而独特的选择性,与其他相关特征无关。这种选择性在两个独立的 fMRI 数据集中都有观察到。这些发现表明,自然社交互动感知会在 STS 中招募专门的神经回路,与心理理论网络分离,是人类社交理解的一个关键维度。