Evidence map›Paper›PMID 38776350›Full record

ArticlePloS one2024

Investigating the neural effects of typicality and predictability for face and object stimuli.

Linda Ficco, Chenglin Li, Jürgen M Kaufmann, Stefan R Schweinberger, Gyula Z Kovács

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Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Linda FiccoDepartment of General Psychology and Cognitive Neuroscience, Friedrich Schiller University, Jena, Germany.ORCID 0000-0001-5005-6430
Chenglin LiDepartment of Biological Psychology and Cognitive Neurosciences, Friedrich Schiller University, Jena, Germany.
Jürgen M KaufmannDepartment of General Psychology and Cognitive Neuroscience, Friedrich Schiller University, Jena, Germany.ORCID 0000-0002-2483-1859
Stefan R SchweinbergerDepartment of General Psychology and Cognitive Neuroscience, Friedrich Schiller University, Jena, Germany.
Gyula Z KovácsDepartment of Biological Psychology and Cognitive Neurosciences, Friedrich Schiller University, Jena, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brain calibrates itself based on the past stimulus diet, which makes frequently observed stimuli appear as typical (as opposed to uncommon stimuli, which appear as distinctive). Based on predictive processing theory, the brain should be more "prepared" for typical exemplars, because these contain information that has been encountered frequently, allowing it to economically represent items of that category. Thus, one could ask whether predictability and typicality of visual stimuli interact, or rather act in an additive manner. We adapted the design by Egner and colleagues (2010), who used cues to induce expectations about stimulus category (face vs. chair) occurrence during an orthogonal inversion detection task. We measured BOLD responses with fMRI in 35 participants. First, distinctive stimuli always elicited stronger responses than typical ones in all ROIs, and our whole-brain directional contrasts for the effects of typicality and distinctiveness converge with previous findings. Second and importantly, we could not replicate the interaction between category and predictability reported by Egner et al. (2010), which casts doubt on whether cueing designs are ideal to elicit reliable predictability effects. Third, likely as a consequence of the lack of predictability effects, we found no interaction between predictability and typicality in any of the four tested regions (bilateral fusiform face areas, lateral occipital complexes) when considering both categories, nor in the whole brain. We discuss the issue of replicability in neuroscience and sketch an agenda for how future studies might address the same question.

Indexed as

BrainMagnetic Resonance ImagingPhotic StimulationAdultBrain MappingCuesFaceFemaleHumansMalePattern Recognition, VisualYoung Adult

Identifiers

PMID38776350
PMCPMC11111078

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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.