Evidence map›Paper›PMID 38104611›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2024

Metaphors or mechanism? Predictive coding and a (brief) history of empirical study of the arts.

Helmut Leder, Matthew Pelowski

Abstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Pragmatic information of aesthetic appraisal.Cognitive neurodynamics · 2025
    Article
  2. Aesthetics and predictive processing: grounds and prospects of a fruitful encounter.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    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

2 authors.

Helmut LederFaculty of Psychology, University of Vienna, Wien 1010, Austria.
Matthew PelowskiFaculty of Psychology, University of Vienna, Wien 1010, Austria.ORCID 0000-0001-5563-3727

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predictive processing (PP) offers an intriguing approach to perception, cognition, but also to appreciation of the arts. It does this by positing both a theoretical basis-one might say a 'metaphor'-for how we engage and respond, placing emphasis on mismatches rather than fluent overlap between schema and environment. Even more, it holds the promise for translating metaphor into neurobiological bases, suggesting a means for considering mechanisms-from basic perceptions to possibly even our complex, aesthetic experiences. However, while we share the excitement of this promise, the history of empirical or psychological aesthetics is also permeated by metaphors that have progressed our understanding but which also tend to elude translation into concrete, mechanistic operationalization-a challenge that can also be made to PP. We briefly consider this difficulty of convincing implementation of PP via a brief historical outline of some developments in the psychological study of aesthetics and art in order to show how these ideas have often anticipated PP but also how they have remained at the level of rather metaphorical and difficult-to-measure concepts. Although theoretical in scope, we hope that this commentary will spur researchers to reflect on PP with the aim of translating metaphorical explanations into well-defined mechanisms in future empirical study. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Indexed as

ArtMetaphorCognitionEstheticsartempirical aestheticspredictive processingtheoretical challenges

Identifiers

PMID38104611
PMCPMC10725760

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Registered trials

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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.