Evidence map›Paper›PMID 27769727›Full record

ReviewTrends in cognitive sciences2016

Making Sense of Real-World Scenes.

George L Malcolm, Iris I A Groen, Chris I Baker

Abstract readReview
In one paragraph

Review in Trends in cognitive sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 1 pooled it
–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

63 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Post-saccadic disruption of semantic category information in naturalistic scenes.Cortex; a journal devoted to the study of the nervous system and behavior · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Generating metamers of human scene understanding.... International Conference on Learning Representations · 2026
    Article
  9. Article
  10. Probing mental representations of space through sketch mapping: a scoping review.Cognitive research: principles and implications · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Representation of locomotive action affordances in human behavior, brains, and deep neural networks.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  17. Cortical Encoding of Spatial Structure and Semantic Content in 3D Natural Scenes.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  18. What Is a Visual Stream?Journal of cognitive neuroscience · 2024
    Article
  19. Graspable foods and tools elicit similar responses in visual cortex.Cerebral cortex (New York, N.Y. : 1991) · 2024
    Article
  20. Article

3 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

3 authors.

George L MalcolmSchool of Psychology, University of East Anglia, Norwich, Norfolk, UK. Electronic address: g.malcolm@uea.ac.uk.
Iris I A GroenLaboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
Chris I BakerLaboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.

Funding

Object, face, body and scene representations in the human brainZIAMH002909 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI BAKER, CHRIS · 2009 to 2025
$25.5M
Object, face and body representations in the human brainZ01MH002909 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI BAKER, CHRISTOPHER · 2008 to 2008
$1.1M
Intramural NIH HHS Z01 MH002909Intramural NIH HHS ZIA MH002909
6 · The paper itself

Abstract

To interact with the world, we have to make sense of the continuous sensory input conveying information about our environment. A recent surge of studies has investigated the processes enabling scene understanding, using increasingly complex stimuli and sophisticated analyses to highlight the visual features and brain regions involved. However, there are two major challenges to producing a comprehensive framework for scene understanding. First, scene perception is highly dynamic, subserving multiple behavioral goals. Second, a multitude of different visual properties co-occur across scenes and may be correlated or independent. We synthesize the recent literature and argue that for a complete view of scene understanding, it is necessary to account for both differing observer goals and the contribution of diverse scene properties.

Indexed as

BrainEnvironmentHumansSensationSpace PerceptionVisual Perception

Identifiers

PMID27769727
PMCPMC5125545

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.