Department of Psychology, Louisiana State University, Baton Rouge, USA; Pennington Biomedical Research Institute, Louisiana State University, Baton Rouge, USA.
Department of Psychiatry, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada; Department of Anatomy & Cell Biology, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada; Neuroscience Program, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada; Brain and Mind Institute, Natural Sciences Centre, University of Western Ontario, London, Ontario, Canada.
Cortex. 2018 Apr;101:31-43. doi: 10.1016/j.cortex.2017.11.016. Epub 2017 Dec 6.
A network of cortical and sub-cortical regions is known to be important in the processing of facial expression. However, to date no study has investigated whether representations of facial expressions present in this network permit generalization across independent samples of face information (e.g., eye region vs mouth region). We presented participants with partial face samples of five expression categories in a rapid event-related fMRI experiment. We reveal a network of face-sensitive regions that contain information about facial expression categories regardless of which part of the face is presented. We further reveal that the neural information present in a subset of these regions: dorsal prefrontal cortex (dPFC), superior temporal sulcus (STS), lateral occipital and ventral temporal cortex, and even early visual cortex, enables reliable generalization across independent visual inputs (faces depicting the 'eyes only' vs 'eyes removed'). Furthermore, classification performance was correlated to behavioral performance in STS and dPFC. Our results demonstrate that both higher (e.g., STS, dPFC) and lower level cortical regions contain information useful for facial expression decoding that go beyond the visual information presented, and implicate a key role for contextual mechanisms such as cortical feedback in facial expression perception under challenging conditions of visual occlusion.
一个已知的在面部表情处理中起重要作用的皮质和皮质下区域网络。然而，迄今为止，尚无研究调查在该网络中呈现的面部表情表示是否允许跨独立的面部信息样本（例如，眼部区域与嘴部区域）进行概括。我们在快速事件相关 fMRI 实验中向参与者展示了五个表情类别的部分面部样本。我们揭示了一个包含有关面部表情类别的信息的面部敏感区域网络，而与呈现的面部哪个部位无关。我们进一步揭示，这些区域中的一部分（背外侧前额叶皮层（dPFC）、颞上沟（STS）、外侧枕叶和腹侧颞叶皮层，甚至早期视觉皮层）中存在的神经信息，可实现对独立视觉输入的可靠概括（仅显示“眼睛”的面孔与“眼睛移除”的面孔）。此外，分类性能与 STS 和 dPFC 中的行为表现相关。我们的结果表明，较高（例如，STS、dPFC）和较低的皮质区域都包含超越呈现的视觉信息有用的面部表情解码信息，并且暗示在视觉遮挡等具有挑战性的条件下，皮质反馈等上下文机制对面部表情感知起着关键作用。
