Evidence map›Paper›PMID 35294241›Full record

ArticleScience advances2022

Brain-like functional specialization emerges spontaneously in deep neural networks.

Katharina Dobs, Julio Martinez, Alexander J E Kell, Nancy Kanwisher

Abstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. The state of modelling face processing in humans with deep learning.British journal of psychology (London, England : 1953) · 2026
    Review
  5. Review
  6. Neural Tuning for Ordinal Processing: Convergent Patterns in Human Brains and Artificial Networks.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  7. The Emergence of Topography and Hemispheric Lateralization in High-Level Vision.Quarterly journal of experimental psychology (2006) · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Sensory encoding of emotion conveyed by the face and visual context.Social cognitive and affective neuroscience · 2026
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. The Representational Organization of Static and Dynamic Visual Features in the Human Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Article

4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Katharina DobsDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-6619-5590
Julio MartinezDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0003-2092-422X
Alexander J E KellZuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
Nancy KanwisherDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0003-3853-7885

Funding

How Does the Functional Organization of the Human Brain Arise in Development?DP1HD091947 · NICHD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KANWISHER, NANCY · 2016 to 2020
$5.4M
NICHD NIH HHS DP1 HD091947
6 · The paper itself

Abstract

The human brain contains multiple regions with distinct, often highly specialized functions, from recognizing faces to understanding language to thinking about what others are thinking. However, it remains unclear why the cortex exhibits this high degree of functional specialization in the first place. Here, we consider the case of face perception using artificial neural networks to test the hypothesis that functional segregation of face recognition in the brain reflects a computational optimization for the broader problem of visual recognition of faces and other visual categories. We find that networks trained on object recognition perform poorly on face recognition and vice versa and that networks optimized for both tasks spontaneously segregate themselves into separate systems for faces and objects. We then show functional segregation to varying degrees for other visual categories, revealing a widespread tendency for optimization (without built-in task-specific inductive biases) to lead to functional specialization in machines and, we conjecture, also brains.

Identifiers

PMID35294241
PMCPMC8926347

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.