Evidence map›Paper›PMID 27832600›Full record

ArticleJournal of neurophysiology2017

Visual search for object categories is predicted by the representational architecture of high-level visual cortex.

Michael A Cohen, George A Alvarez, Ken Nakayama, Talia Konkle

Abstract read
In one paragraph

Article in Journal of neurophysiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
  2. Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
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  17. Review
  18. Article
  19. Category Trumps Shape as an Organizational Principle of Object Space in the Human Occipitotemporal Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  20. Disentangling Object Category Representations Driven by Dynamic and Static Visual Input.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
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.

Michael A CohenMcGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts; and michaelthecohen@gmail.com.
George A AlvarezDepartment of Psychology, Harvard University, Cambridge, Massachusetts.
Ken NakayamaDepartment of Psychology, Harvard University, Cambridge, Massachusetts.
Talia KonkleDepartment of Psychology, Harvard University, Cambridge, Massachusetts.

Funding

The Role of Animacy and Size in the Neural Organization of Object KnowledgeF32EY022863 · NEI · HARVARD UNIVERSITY · PI KONKLE, TALIA · 2013 to 2015
$114k
NEI NIH HHS F32 EY022863
6 · The paper itself

Abstract

Visual search is a ubiquitous visual behavior, and efficient search is essential for survival. Different cognitive models have explained the speed and accuracy of search based either on the dynamics of attention or on similarity of item representations. Here, we examined the extent to which performance on a visual search task can be predicted from the stable representational architecture of the visual system, independent of attentional dynamics. Participants performed a visual search task with 28 conditions reflecting different pairs of categories (e.g., searching for a face among cars, body among hammers, etc.). The time it took participants to find the target item varied as a function of category combination. In a separate group of participants, we measured the neural responses to these object categories when items were presented in isolation. Using representational similarity analysis, we then examined whether the similarity of neural responses across different subdivisions of the visual system had the requisite structure needed to predict visual search performance. Overall, we found strong brain/behavior correlations across most of the higher-level visual system, including both the ventral and dorsal pathways when considering both macroscale sectors as well as smaller mesoscale regions. These results suggest that visual search for real-world object categories is well predicted by the stable, task-independent architecture of the visual system. NEW & NOTEWORTHY: Here, we ask which neural regions have neural response patterns that correlate with behavioral performance in a visual processing task. We found that the representational structure across all of high-level visual cortex has the requisite structure to predict behavior. Furthermore, when directly comparing different neural regions, we found that they all had highly similar category-level representational structures. These results point to a ubiquitous and uniform representational structure in high-level visual cortex underlying visual object processing.

Indexed as

Brain MappingAdolescentAdultAttentionFemaleHumansImage Processing, Computer-AssistedLinear ModelsMagnetic Resonance ImagingMaleNerve NetNeural PathwaysOxygenPhotic StimulationReaction TimeVisual CortexOxygenbrain/behavior correlationscognitionfMRIrepresentational similarity analysisvision

Identifiers

PMID27832600
PMCPMC5236111

What OpenQuestion holds

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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.