ArticleCommunications biology2022
Face identity coding in the deep neural network and primate brain.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 26 citations in OpenAlex.
- Category selectivity observed in the human brain is distinct from category selectivity observed in artificial neural networks.bioRxiv : the preprint server for biology · 2026Article
- Characterization of the spatiotemporal representations of visual, semantic, and memorability features in the human brain.PLoS biology · 2026Article
- A neural computational framework for face processing in the human temporal lobe.Current biology : CB · 2025Article
- Decoding dynamic visual scenes across the brain hierarchy.PLoS computational biology · 2024Article
- Encoding of Visual Objects in the Human Medial Temporal Lobe.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Deep social neuroscience: the promise and peril of using artificial neural networks to study the social brain.Social cognitive and affective neuroscience · 2024Review
- A critical period for developing face recognition.Patterns (New York, N.Y.) · 2024Article
- Neural mechanisms of face familiarity and learning in the human amygdala and hippocampus.Cell reports · 2024Article
- Can micro-expressions be used as a biomarker for autism spectrum disorder?Frontiers in neuroinformatics · 2024Article
- Using multi-task experiments to test principles of hippocampal function.Hippocampus · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
A central challenge in face perception research is to understand how neurons encode face identities. This challenge has not been met largely due to the lack of simultaneous access to the entire face processing neural network and the lack of a comprehensive multifaceted model capable of characterizing a large number of facial features. Here, we addressed this challenge by conducting in silico experiments using a pre-trained face recognition deep neural network (DNN) with a diverse array of stimuli. We identified a subset of DNN units selective to face identities, and these identity-selective units demonstrated generalized discriminability to novel faces. Visualization and manipulation of the network revealed the importance of identity-selective units in face recognition. Importantly, using our monkey and human single-neuron recordings, we directly compared the response of artificial units with real primate neurons to the same stimuli and found that artificial units shared a similar representation of facial features as primate neurons. We also observed a region-based feature coding mechanism in DNN units as in human neurons. Together, by directly linking between artificial and primate neural systems, our results shed light on how the primate brain performs face recognition tasks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.