Evidence map›Paper›PMID 42567913›Full record

ArticleScientific reports2026

Category-based attention facilitates the recognition of actions.

Federica Danaj, Lena Geßele, Jens Schwarzbach, Paul Downing, Angelika Lingnau

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Federica DanajChair of Cognitive Neuroscience, University of Regensburg, Regensburg, Germany.
Lena GeßeleChair of Cognitive Neuroscience, University of Regensburg, Regensburg, Germany.
Jens SchwarzbachDepartment of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
Paul DowningDepartment of Psychology, Bangor University, Bangor, Wales.
Angelika LingnauChair of Cognitive Neuroscience, University of Regensburg, Regensburg, Germany. angelika.lingnau@ur.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Action recognition relies on efficiently prioritizing relevant sources of information. This study examined the degree to which category-based attention facilitates the identification of basic action categories (climb, jump, run, walk) depicted as static avatar images (Exp. 1, 2) and naturalistic images (Exp. 3, 4). Participants received prior information about the target action category through a word cue (Exp. 1, 2, 4) or an avatar image cue (Exp. 3), with a 3:1 ratio of valid to invalid trials. Performance was assessed in terms of accuracy, reaction time (RT), and sensitivity (d-prime). Exp. 1 revealed a cueing effect of word cues on processing subsequent avatar stimuli that depicted different actions. Exp. 2 confirmed that this facilitation was due to the cue itself rather than specific motor associations. Exp. 3 indicated that avatar cues aid action recognition in naturalistic images, though the effect was weaker and limited to accuracy. Exp. 4 combined word cues with the same naturalistic images and revealed robust cueing effects on both accuracy and RT, indicating that top-down facilitation is preserved for naturalistic stimuli when word cues are used. Together, these findings provide an important extension of previous studies, suggesting that category-based attention enhances action recognition by pre-activating relevant action representations.

Indexed as

AttentionPattern Recognition, VisualRecognition, PsychologyAdultAvatarCuesFemaleHumansMalePhotic StimulationReaction TimeYoung AdultAction recognitionAttentional templatesCategory-based attentionTop-down attentionVisual attention

Identifiers

PMID42567913
PMCPMC13451218

What OpenQuestion holds

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LicenceCC BY
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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.