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  4. A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans

A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans

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Author(s)
Farzmahdi, Amirhossein
•
Rajaei, Karim
•
Ghodrati, Masoud
•
Ebrahimpour, Reza
•
Khaligh Razavi, Seyed Mahdi
Date Issued
April 2016
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Farzmahdi, Amirhossein et al. “A Specialized Face-Processing Model Inspired by the Organization of Monkey Face Patches Explains Several Face-Specific Phenomena Observed in Humans.” Scientific Reports 6.1 (2016): n. pag. © 2017 Macmillan Publishers Limited
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Final published version
Abstract
Converging reports indicate that face images are processed through specialized neural networks in the brain –i.e. face patches in monkeys and the fusiform face area (FFA) in humans. These studies were designed to find out how faces are processed in visual system compared to other objects. Yet, the underlying mechanism of face processing is not completely revealed. Here, we show that a hierarchical computational model, inspired by electrophysiological evidence on face processing in primates, is able to generate representational properties similar to those observed in monkey face patches (posterior, middle and anterior patches). Since the most important goal of sensory neuroscience is linking the neural responses with behavioral outputs, we test whether the proposed model, which is designed to account for neural responses in monkey face patches, is also able to predict well-documented behavioral face phenomena observed in humans. We show that the proposed model satisfies several cognitive face effects such as: composite face effect and the idea of canonical face views. Our model provides insights about the underlying computations that transfer visual information from posterior to anterior face patches.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Creative Commons Attribution
http://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/109029
DOI of Published Version
https://doi.org/10.1038/srep25025
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