The Functional Neuroanatomy of Face Processing: Insights from Neuroimaging and Implications for Deep Learning

Citation data:

Deep Learning for Biometrics, ISSN: 2191-6586, Vol: PartF1, Page: 3-31

Publication Year:
2017
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DOI:
10.1007/978-3-319-61657-5_1
Author(s):
Kalanit Grill-Spector, Kendrick Kay, Kevin S. Weiner
Publisher(s):
Springer Nature
Tags:
Computer Science
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book chapter description
Face perception is critical for normal social functioning, and is mediated by a cortical network of regions in the ventral visual stream. Comparative analysis between present deep neural network architectures for biometrics and neural architectures in the human brain is necessary for developing artificial systems with human abilities. Neuroimaging research has advanced our understanding regarding the functional architecture of the human ventral face network. Here, we describe recent neuroimaging findings in three domains: (1) the macro- and microscopic anatomical features of the ventral face network in the human brain, (2) the characteristics of white matter connections, and (3) the basic computations performed by population receptive fields within face-selective regions composing this network. Then, we consider how empirical findings can inform the development of accurate computational deep neural networks for face recognition as well as shed light on computational benefits of specific neural implementational features.

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