Representational Dynamics of Facial Viewpoint Encoding

被引:18
作者
Kietzmann, Tim C. [1 ,2 ]
Gert, Anna L. [2 ]
Tong, Frank [3 ]
Koenig, Peter [2 ,4 ]
机构
[1] MRC, Cambridge, England
[2] Univ Osnabruck, Osnabruck, Germany
[3] Vanderbilt Univ, 221 Kirkland Hall, Nashville, TN 37235 USA
[4] Univ Med Ctr Hamburg Eppendorf, Hamburg, Germany
基金
欧洲研究理事会; 欧盟地平线“2020”;
关键词
FUSIFORM FACE AREA; HUMAN VISUAL-CORTEX; INFERIOR TEMPORAL CORTEX; LEVEL IMAGE PROPERTIES; 3-DIMENSIONAL OBJECT RECOGNITION; HUMAN NEURAL SYSTEM; DISTINCT REPRESENTATIONS; RESPONSE PROPERTIES; CONTRAST-REVERSAL; SELECTIVE REGIONS;
D O I
10.1162/jocn_a_01070
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Faces provide a wealth of information, including the identity of the seen person and social cues, such as the direction of gaze. Crucially, different aspects of face processing require distinct forms of information encoding. Another person's attentional focus can be derived based on a view-dependent code. In contrast, identification benefits from invariance across all viewpoints. Different cortical areas have been suggested to subserve these distinct functions. However, little is known about the temporal aspects of differential viewpoint encoding in the human brain. Here, we combine EEG with multivariate data analyses to resolve the dynamics of face processing with high temporal resolution. This revealed a distinct sequence of view-point encoding. Head orientations were encoded first, starting after around 60 msec of processing. Shortly afterward, peaking around 115 msec after stimulus onset, a different encoding scheme emerged. At this latency, mirror-symmetric viewing angles elicited highly similar cortical responses. Finally, about 280 msec after visual onset, EEG response patterns demonstrated a considerable degree of viewpoint invariance across all viewpoints tested, with the noteworthy exception of the front-facing view. Taken together, our results indicate that the processing of facial viewpoints follows a temporal sequence of encoding schemes, potentially mirroring different levels of computational complexity.
引用
收藏
页码:637 / 651
页数:15
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