FFA and OFA Encode Distinct Types of Face Identity Information

被引:41
|
作者
Tsantani, Maria [1 ,5 ]
Kriegeskorte, Nikolaus [2 ]
Storrs, Katherine [3 ]
Williams, Adrian Lloyd [1 ]
McGettigan, Carolyn [4 ]
Garrido, Lucia [1 ,6 ]
机构
[1] Brunel Univ London, Dept Life Sci, Div Psychol, Uxbridge UB8 3PH, Middx, England
[2] Columbia Univ, Zuckerman Mind Brain Behav Inst, New York, NY 10027 USA
[3] Justus Liebig Univ, Dept Expt Psychol, D-35390 Giessen, Germany
[4] UCL, Speech Hearing & Phonet Sci, London WC1N 1PF, England
[5] Birkbeck Univ London, Dept Psychol Sci, London WCE 7HX, England
[6] City Univ London, Dept Psychol, London EC1V 0HB, England
来源
JOURNAL OF NEUROSCIENCE | 2021年 / 41卷 / 09期
关键词
face identity; face processing; FFA; OFA; representational similarity analysis; SURFACE REFLECTANCE; TEMPORAL CORTEX; FACIAL IDENTITY; NEURAL ACTIVITY; REPRESENTATIONS; PERCEPTION; SELECTIVITY; SIMILARITY; PATTERNS; FEATURES;
D O I
10.1523/JNEUROSCI.1449-20.2020
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Faces of different people elicit distinct fMRI patterns in several face-selective regions of the human brain. Here we used rep-resentational similarity analysis to investigate what type of identity-distinguishing information is encoded in three face-selec-tive regions: fusiform face area (FFA), occipital face area (OFA), and posterior superior temporal sulcus (pSTS). In a sample of 30 human participants (22 females, 8 males), we used fMRI to measure brain activity patterns elicited by naturalistic vid-eos of famous face identities, and compared their representational distances in each region with models of the differences between identities. We built diverse candidate models, ranging from low-level image-computable properties (pixel-wise, GIST, and Gabor-Jet dissimilarities), through higher-level image-computable descriptions (OpenFace deep neural network, trained to cluster faces by identity), to complex human-rated properties (perceived similarity, social traits, and gender). We found marked differences in the information represented by the FFA and OFA. Dissimilarities between face identities in FFA were accounted for by differences in perceived similarity, Social Traits, Gender, and by the OpenFace network. In contrast, repre-sentational distances in OFA were mainly driven by differences in low-level image-based properties (pixel-wise and Gabor-Jet dissimilarities). Our results suggest that, although FFA and OFA can both discriminate between identities, the FFA represen-tation is further removed from the image, encoding higher-level perceptual and social face information.
引用
收藏
页码:1952 / 1969
页数:18
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