Dynamic and static facial expressions decoded from motion-sensitive areas in the macaque monkey.
Dynamic and static facial expressions decoded from motion-sensitive areas in the macaque monkey.
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DOI：
10.1523/jneurosci.1992-12.2012
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发表时间：
2012-11-07
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影响因子：
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通讯作者：
Ungerleider LG
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作者：
Furl N;Hadj-Bouziane F;Liu N;Averbeck BB;Ungerleider LG
人类熟练地使用视觉运动来识别与社会相关的面部信息。猕猴的上级颞沟（STS）具有对面部和视觉运动敏感的脑区的选择性，为研究表情运动的神经编码提供了一个模型视觉系统。我们采用功能性磁共振成像和面部刺激来定位运动敏感区（Mf区），与静态面部相比，运动敏感区对动态面部的反应更大，而面部选择性区域则选择性地对物体和地点的面部做出反应。使用多变量分析，我们发现，有关动态和静态面部表情的信息可以鲁棒地解码Mf区域。相比之下，面部选择性区域表现出相对较少的面部表情信息。用一种运动类型（动态或静态）的表达训练的分类器对另一种运动类型表现出较差的泛化能力，这表明Mf区域采用单独的和不可混淆的神经代码来动态和静态呈现相同的表达。我们还表明，面部刺激引起的一些运动敏感性是不特定的脸，但也可以引起移动点，特别是在FST和STPm/LST，确认他们已经建立了良好的低水平的运动敏感性。一个不同的模式被发现在前STS，这对动态比静态的脸，但不敏感的点运动。总的来说，我们发现情绪表达主要表现在面部选择皮层之外，对运动敏感的区域。这些区域可能在增强面部表情识别方面发挥重要作用，尽管与运动相关的复杂刺激变化。
Humans adeptly use visual motion to recognize socially-relevant facial information. The macaque provides a model visual system for studying neural coding of expression movements, as its superior temporal sulcus (STS) possesses brain areas selective for faces and areas sensitive to visual motion. We employed functional magnetic resonance imaging and facial stimuli to localize motion-sensitive areas (Mf areas), which responded more to dynamic faces compared to static faces, and face-selective areas, which responded selectively to faces compared to objects and places. Using multivariate analysis, we found that information about both dynamic and static facial expressions could be robustly decoded from Mf areas. By contrast, face-selective areas exhibited relatively less facial expression information. Classifiers trained with expressions from one motion type (dynamic or static) showed poor generalization to the other motion type, suggesting that Mf areas employ separate and non-confusable neural codes for dynamic and static presentations of the same expressions. We also show that some of the motion sensitivity elicited by facial stimuli was not specific to faces but could also be elicited by moving dots, particularly in FST and STPm/LST, confirming their already well-established low-level motion sensitivity. A different pattern was found in anterior STS, which responded more to dynamic than static faces but was not sensitive to dot motion. Overall, we show that emotional expressions are mostly represented outside of face-selective cortex, in areas sensitive to motion. These regions may play a fundamental role in enhancing recognition of facial expression despite the complex stimulus changes associated with motion.