Department of Psychology and York Neuroimaging Centre, University of York, York, United Kingdom.
Department of Psychology and York Neuroimaging Centre, University of York, York, United Kingdom.
Cortex. 2018 Jun;103:199-210. doi: 10.1016/j.cortex.2018.03.009. Epub 2018 Mar 23.
Models of face processing suggest that the neural response in different face regions is selective for higher-level attributes of the face, such as identity and expression. However, it remains unclear to what extent the response in these regions can also be explained by more basic organizing principles. Here, we used functional magnetic resonance imaging multivariate pattern analysis (fMRI-MVPA) to ask whether spatial patterns of response in the core face regions (occipital face area - OFA, fusiform face area - FFA, superior temporal sulcus - STS) can be predicted across different participants by lower level properties of the stimulus. First, we compared the neural response to face identity and viewpoint, by showing images of different identities from different viewpoints. The patterns of neural response in the core face regions were predicted by the viewpoint, but not the identity of the face. Next, we compared the neural response to viewpoint and expression, by showing images with different expressions from different viewpoints. Again, viewpoint, but not expression, predicted patterns of response in face regions. Finally, we show that the effect of viewpoint in both experiments could be explained by changes in low-level image properties. Our results suggest that a key determinant of the neural representation in these core face regions involves lower-level image properties rather than an explicit representation of higher-level attributes in the face. The advantage of a relatively image-based representation is that it can be used flexibly in the perception of faces.
面部处理模型表明，不同面部区域的神经反应是对面部更高层次属性（如身份和表情）的选择性反应。然而，这些区域的反应在多大程度上也可以用更基本的组织原则来解释，目前仍不清楚。在这里，我们使用功能磁共振成像多变量模式分析（fMRI-MVPA）来询问核心面部区域（枕叶面部区域-OFA、梭状回面部区域-FFA、颞上沟-STS）中的反应空间模式是否可以通过刺激的较低水平属性在不同参与者之间进行预测。首先，我们通过显示不同视角的不同身份的图像来比较身份和视角对面部身份的神经反应。核心面部区域的神经反应模式由视角预测，但不是面部的身份。接下来，我们通过显示不同视角和表情的图像来比较视角和表情对面部表情的神经反应。同样，是视角，而不是表情，预测了面部区域的反应模式。最后，我们表明，两个实验中视角的影响都可以用低水平图像属性的变化来解释。我们的研究结果表明，这些核心面部区域中神经表示的一个关键决定因素涉及较低水平的图像属性，而不是面部中较高层次属性的明确表示。基于图像的表示的优点是它可以灵活地用于对面部的感知。
