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Trends Cogn Sci. 2017 Dec;21(12):915-916. doi: 10.1016/j.tics.2017.09.007. Epub 2017 Sep 19.

Reading Faces: From Features to Recognition.

Author information

1
Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA; Center for Cognitive Neuroscience at Dartmouth, Dartmouth College, Hanover, NH, USA; Vicarious AI, Union City, CA, USA. Electronic address: swaroopgj@gmail.com.
2
Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA; Center for Cognitive Neuroscience at Dartmouth, Dartmouth College, Hanover, NH, USA; Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale (DIMES), Medical School, University of Bologna, Bologna, Italy. Electronic address: maria.i.gobbini@dartmouth.edu.

Abstract

Chang and Tsao recently reported that the monkey face patch system encodes facial identity in a space of facial features as opposed to exemplars. Here, we discuss how such coding might contribute to face recognition, emphasizing the critical role of learning and interactions with other brain areas for optimizing the recognition of familiar faces.

KEYWORDS:

code for face identity; face learning; face recognition; facial features; primate face processing system; view-invariant identity

PMID:
28939331
DOI:
10.1016/j.tics.2017.09.007
[Indexed for MEDLINE]

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