Evidence map›Paper›PMID 31484756›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

The default-mode network represents aesthetic appeal that generalizes across visual domains.

Edward A Vessel, Ayse Ilkay Isik, Amy M Belfi, Jonathan L Stahl, G Gabrielle Starr

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
6.9field-weighted citation impact, top 2% of its field
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

42 citing papers in PubMed, 122 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Being moved by modern abstract art.Frontiers in psychology · 2026
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. The Beholder's Share: Bridging art and neuroscience to study individual differences in subjective experience.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

5 authors at 4 institutions in 2 countries.

Edward A VesselDepartment of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main 60322, Germany; ed.vessel@ae.mpg.de.ORCID 0000-0001-8733-1731
Ayse Ilkay IsikDepartment of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main 60322, Germany.
Amy M BelfiDepartment of Psychological Science, Missouri University of Science and Technology, Rolla, MO 65409.
Jonathan L StahlDepartment of Psychology, The Ohio State University, Columbus, OH 43210.
G Gabrielle StarrDepartments of English and Neuroscience, Pomona College, Claremont, CA 91711.
Max Planck Institute for Empirical Aesthetics · DEMissouri University of Science and Technology · USPomona College · USThe Ohio State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visual aesthetic evaluations, which impact decision-making and well-being, recruit the ventral visual pathway, subcortical reward circuitry, and parts of the medial prefrontal cortex overlapping with the default-mode network (DMN). However, it is unknown whether these networks represent aesthetic appeal in a domain-general fashion, independent of domain-specific representations of stimulus content (artworks versus architecture or natural landscapes). Using a classification approach, we tested whether the DMN or ventral occipitotemporal cortex (VOT) contains a domain-general representation of aesthetic appeal. Classifiers were trained on multivoxel functional MRI response patterns collected while observers made aesthetic judgments about images from one aesthetic domain. Classifier performance (high vs. low aesthetic appeal) was then tested on response patterns from held-out trials from the same domain to derive a measure of domain-specific coding, or from a different domain to derive a measure of domain-general coding. Activity patterns in category-selective VOT contained a degree of domain-specific information about aesthetic appeal, but did not generalize across domains. Activity patterns from the DMN, however, were predictive of aesthetic appeal across domains. Importantly, the ability to predict aesthetic appeal varied systematically; predictions were better for observers who gave more extreme ratings to images subsequently labeled as "high" or "low." These findings support a model of aesthetic appreciation whereby domain-specific representations of the content of visual experiences in VOT feed in to a "core" domain-general representation of visual aesthetic appeal in the DMN. Whole-brain "searchlight" analyses identified additional prefrontal regions containing information relevant for appreciation of cultural artifacts (artwork and architecture) but not landscapes.

Indexed as

AdultBrainBrain MappingCerebral CortexEstheticsFemaleHumansJudgmentMagnetic Resonance ImagingMaleNerve NetVisual PathwaysVisual Perceptionarchitectureartworkdefault-mode networknatural landscapevisual aesthetics

Identifiers

PMID31484756
PMCPMC6754616
OpenAlexW2971420668

What OpenQuestion holds

Textmetadata
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.