Evidence map›Paper›PMID 34411847›Full record

ArticleCortex; a journal devoted to the study of the nervous system and behavior2021

Cortical networks of dynamic scene category representation in the human brain.

Emin Çelik, Umit Keles, İbrahim Kiremitçi, Jack L Gallant, Tolga Çukur

Abstract read
In one paragraph

Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. 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
  2. Movie Features Are Hierarchically Encoded in the Dynamics of Functional Connectivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Article
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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

5 authors.

Emin ÇelikNeuroscience Program, Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey; National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey. Electronic address: emin.celik@bilkent.edu.tr.
Umit KelesNational Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey; Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.
İbrahim KiremitçiNeuroscience Program, Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey; National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey.
Jack L GallantHelen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA; Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA; Department of Psychology, University of California, Berkeley, CA, USA.
Tolga ÇukurNeuroscience Program, Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey; National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey; Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey.

Funding

Visual Representation and AttentionR01EY019684 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI GALLANT, JACK L · 2010 to 2018
$2.9M
NEI NIH HHS R01 EY019684
6 · The paper itself

Abstract

Humans have an impressive ability to rapidly process global information in natural scenes to infer their category. Yet, it remains unclear whether and how scene categories observed dynamically in the natural world are represented in cerebral cortex beyond few canonical scene-selective areas. To address this question, here we examined the representation of dynamic visual scenes by recording whole-brain blood oxygenation level-dependent (BOLD) responses while subjects viewed natural movies. We fit voxelwise encoding models to estimate tuning for scene categories that reflect statistical ensembles of objects and actions in the natural world. We find that this scene-category model explains a significant portion of the response variance broadly across cerebral cortex. Cluster analysis of scene-category tuning profiles across cortex reveals nine spatially-segregated networks of brain regions consistently across subjects. These networks show heterogeneous tuning for a diverse set of dynamic scene categories related to navigation, human activity, social interaction, civilization, natural environment, non-human animals, motion-energy, and texture, suggesting that the organization of scene category representation is quite complex.

Indexed as

Cerebral CortexMagnetic Resonance ImagingBrainBrain MappingCluster AnalysisHumansPattern Recognition, VisualPhotic StimulationVisual PerceptionCluster analysisDynamic scene category representationfMRIVoxelwise encoding model

Identifiers

PMID34411847
PMCPMC8501312

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.