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Feature-based encoding of face identity by single neurons in the human medial temporal lobe

Runnan Cao, Jinge Wang, Chujun Lin, Ueli Rutishauser, Alexander Todorov, Xin Li, Nicholas Brandmeir, Shuo Wang
doi: https://doi.org/10.1101/2020.09.01.278283
Runnan Cao
1Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, WV 26506, USA
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  • For correspondence: runnan.cao@mail.wvu.edu wangshuo45@gmail.com
Jinge Wang
2Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
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Chujun Lin
3Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA
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Ueli Rutishauser
4Departments of Neurosurgery and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
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Alexander Todorov
5Department of Psychology and Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
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Xin Li
2Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
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Nicholas Brandmeir
6Department of Neurosurgery, West Virginia University, Morgantown, WV 26506, USA
7Rockefeller Neurosciences Institute, West Virginia University, Morgantown, WV 26506, USA
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Shuo Wang
1Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, WV 26506, USA
7Rockefeller Neurosciences Institute, West Virginia University, Morgantown, WV 26506, USA
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  • For correspondence: runnan.cao@mail.wvu.edu wangshuo45@gmail.com
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Abstract

Neurons in the human medial temporal lobe (MTL) that are selective for the identity of specific people are classically thought to encode identity invariant to visual features. However, it remains largely unknown how visual information from higher visual cortex is translated into a semantic representation of an individual person. Here, we show that some MTL neurons are selective to multiple different face identities on the basis of shared features that form clusters in the representation of a deep neural network trained to recognize faces. Contrary to prevailing views, we find that these neurons represent an individual’s face with feature-based encoding, rather than through association with concepts. The response of feature neurons did not depend on face identity nor face familiarity, and the region of feature space to which they are tuned predicted their response to new face stimuli. Our results provide critical evidence bridging the perception-driven representation of facial features in the higher visual cortex and the memory-driven representation of semantics in the MTL, which may form the basis for declarative memory.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 02, 2020.
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Feature-based encoding of face identity by single neurons in the human medial temporal lobe
Runnan Cao, Jinge Wang, Chujun Lin, Ueli Rutishauser, Alexander Todorov, Xin Li, Nicholas Brandmeir, Shuo Wang
bioRxiv 2020.09.01.278283; doi: https://doi.org/10.1101/2020.09.01.278283
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Feature-based encoding of face identity by single neurons in the human medial temporal lobe
Runnan Cao, Jinge Wang, Chujun Lin, Ueli Rutishauser, Alexander Todorov, Xin Li, Nicholas Brandmeir, Shuo Wang
bioRxiv 2020.09.01.278283; doi: https://doi.org/10.1101/2020.09.01.278283

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