Evidence map›Paper›PMID 30543845›Full record

ArticleNeuroImage2019

Dynamics of aesthetic experience are reflected in the default-mode network.

Amy M Belfi, Edward A Vessel, Aenne Brielmann, Ayse Ilkay Isik, Anjan Chatterjee, Helmut Leder, Denis G Pelli, G Gabrielle Starr

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 2 pooled it
6.5field-weighted citation impact, top 3% 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

40 citing papers in PubMed, 2 syntheses or guidelines pooled it, 128 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. The psychophysics of style.Nature human behaviour · 2025
    Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Modelling individual aesthetic judgements over time.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  19. Metaphors or mechanism? Predictive coding and a (brief) history of empirical study of the arts.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  20. Review
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

8 authors at 6 institutions in 3 countries.

Amy M BelfiDepartment of Psychological Science, Missouri University of Science and Technology, Rolla, MO, USA. Electronic address: amybelfi@mst.edu.
Edward A VesselDepartment of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany. Electronic address: ed.vessel@ae.mpg.de.
Aenne BrielmannDepartment of Psychology, New York University, New York, NY, USA.
Ayse Ilkay IsikDepartment of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany.
Anjan ChatterjeeDepartment of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Helmut LederDepartment of Basic Psychological Research and Research Methods, University of Vienna, Vienna, Austria.
Denis G PelliDepartment of Psychology, New York University, New York, NY, USA.
G Gabrielle StarrDepartment of English, Pomona College, Claremont, CA, USA.
Max Planck Institute for Empirical Aesthetics · DENew York University · USMissouri University of Science and Technology · USPomona College · USUniversity of Pennsylvania · USUniversity of Vienna · AT

Funding

Vision Core Grant- Design and Fabrication ModuleP30EY013079 · NEI · NEW YORK UNIVERSITY · PI MOVSHON, J ANTHONY · 2000 to 2025
$14.2M
TRANSMISSION OF INFORMATION IN VISUAL SYSTEMR01EY004432 · NEI · SYRACUSE UNIVERSITY AT SYRACUSE · PI PELLI, DENIS G · 1985 to 2010
$2.1M
NEI NIH HHS P30 EY013079NEI NIH HHS R01 EY004432
6 · The paper itself

Abstract

Neuroaesthetics is a rapidly developing interdisciplinary field of research that aims to understand the neural substrates of aesthetic experience: While understanding aesthetic experience has been an objective of philosophers for centuries, it has only more recently been embraced by neuroscientists. Recent work in neuroaesthetics has revealed that aesthetic experience with static visual art engages visual, reward and default-mode networks. Very little is known about the temporal dynamics of these networks during aesthetic appreciation. Previous behavioral and brain imaging research suggests that critical aspects of aesthetic experience have slow dynamics, taking more than a few seconds, making them amenable to study with fMRI. Here, we identified key aspects of the dynamics of aesthetic experience while viewing art for various durations. In the first few seconds following image onset, activity in the DMN (and high-level visual and reward regions) was greater for very pleasing images; in the DMN this activity counteracted a suppressive effect that grew longer and deeper with increasing image duration. In addition, for very pleasing art, the DMN response returned to baseline in a manner time-locked to image offset. Conversely, for non-pleasing art, the timing of this return to baseline was inconsistent. This differential response in the DMN may therefore reflect the internal dynamics of the participant's state: The participant disengages from art-related processing and returns to stimulus-independent thought. These dynamics suggest that the DMN tracks the internal state of a participant during aesthetic experience.

Indexed as

BeautyAdultCerebral CortexEstheticsFemaleFunctional NeuroimagingHumansMagnetic Resonance ImagingMaleNerve NetPaintingsPattern Recognition, VisualPleasureYoung Adult

Identifiers

PMID30543845
PMCPMC8493917
OpenAlexW2904750937

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.