ArticleeLife2020
The neurons that mistook a hat for a face.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- Brainana: an end-to-end preprocessing framework for macaque neuroimaging.bioRxiv : the preprint server for biology · 2026Article
- Article
- Processing of natural scenes in the human pulvinar.Nature communications · 2025Article
- Effects of Partial Occlusion on Response Dynamics and Interregional Processing within Primate Superior Temporal Sulcus.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Article
- Brain feature maps reveal progressive animal-feature representations in the ventral stream.Science advances · 2025Article
- Face pareidolia minimally engages macaque face selective neurons.Progress in neurobiology · 2025Article
- An Eccentricity Gradient Reversal across High-Level Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Face cells encode object parts more than facial configuration of illusory faces.Nature communications · 2024Article
- Neural Encoding of Bodies for Primate Social Perception.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- Neuronal Mechanisms Underlying Face Recognition in Non-human Primates.The Japanese psychological research · 2024Article
- Inactivation of face-selective neurons alters eye movements when free viewing faces.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Configuration-sensitive face-body interactions in primate visual cortex.Progress in neurobiology · 2024Article
- Species-specific wiring of cortical circuits for small-world networks in the primary visual cortex.PLoS computational biology · 2023Article
- Color-biased regions in the ventral visual pathway are food selective.Current biology : CB · 2023Article
- Categorization learning induced changes in action representations in the macaque STS.NeuroImage · 2023Article
- One object, two networks? Assessing the relationship between the face and body-selective regions in the primate visual system.Brain structure & function · 2022Review
- A Distributed Model of Face and Body Integration.Neuroscience insights · 2022Article
- Holistic face recognition is an emergent phenomenon of spatial processing in face-selective regions.Nature communications · 2021Article
- The macaque face patch system: a turtle's underbelly for the brain.Nature reviews. Neuroscience · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Despite evidence that context promotes the visual recognition of objects, decades of research have led to the pervasive notion that the object processing pathway in primate cortex consists of multiple areas that each process the intrinsic features of a few particular categories (e.g. faces, bodies, hands, objects, and scenes). Here we report that such category-selective neurons do not in fact code individual categories in isolation but are also sensitive to object relationships that reflect statistical regularities of the experienced environment. We show by direct neuronal recording that face-selective neurons respond not just to an image of a face, but also to parts of an image where contextual cues-for example a body-indicate a face ought to be, even if what is there is not a face.
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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.