A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans
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 u...
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Nature Publishing Group
2017
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Online Access: | http://hdl.handle.net/1721.1/109029 https://orcid.org/0000-0002-5700-1704 |
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author | Farzmahdi, Amirhossein Rajaei, Karim Ghodrati, Masoud Ebrahimpour, Reza Khaligh Razavi, Seyed Mahdi |
author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Farzmahdi, Amirhossein Rajaei, Karim Ghodrati, Masoud Ebrahimpour, Reza Khaligh Razavi, Seyed Mahdi |
author_sort | Farzmahdi, Amirhossein |
collection | MIT |
description | 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. |
first_indexed | 2024-09-23T12:36:36Z |
format | Article |
id | mit-1721.1/109029 |
institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T12:36:36Z |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | dspace |
spelling | mit-1721.1/1090292022-09-28T09:00:32Z A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans Farzmahdi, Amirhossein Rajaei, Karim Ghodrati, Masoud Ebrahimpour, Reza Khaligh Razavi, Seyed Mahdi Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Khaligh Razavi, Seyed Mahdi 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. 2017-05-11T21:11:27Z 2017-05-11T21:11:27Z 2016-04 2015-09 Article http://purl.org/eprint/type/JournalArticle 2045-2322 http://hdl.handle.net/1721.1/109029 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 https://orcid.org/0000-0002-5700-1704 en_US http://dx.doi.org/10.1038/srep25025 Scientific Reports Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature Publishing Group |
spellingShingle | Farzmahdi, Amirhossein Rajaei, Karim Ghodrati, Masoud Ebrahimpour, Reza Khaligh Razavi, Seyed Mahdi A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans |
title | A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans |
title_full | A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans |
title_fullStr | A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans |
title_full_unstemmed | A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans |
title_short | A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans |
title_sort | specialized face processing model inspired by the organization of monkey face patches explains several face specific phenomena observed in humans |
url | http://hdl.handle.net/1721.1/109029 https://orcid.org/0000-0002-5700-1704 |
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