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2017 | OriginalPaper | Chapter

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

Authors : Kalanit Grill-Spector, Kendrick Kay, Kevin S. Weiner

Published in: Deep Learning for Biometrics

Publisher: Springer International Publishing

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Abstract

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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Appendix
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Footnotes
1
See Appendix for abbreviations and definitions.
 
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Metadata
Title
The Functional Neuroanatomy of Face Processing: Insights from Neuroimaging and Implications for Deep Learning
Authors
Kalanit Grill-Spector
Kendrick Kay
Kevin S. Weiner
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-61657-5_1

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