Evidence map›Paper›PMID 40750969›Full record

ArticleScientific reports2025

The role of cognitive load in automatic integration of emotional information from face and body.

Anne-Sophie Puffet, Simon Rigoulot

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. Article
  2. 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.

Anne-Sophie PuffetDepartment of Psychology, University of Quebec at Trois-Rivières, Trois-Rivières, Canada. anne-sophie.puffet@uqtr.ca.ORCID http://orcid.org/0000-0001-9352-2526
Simon RigoulotDepartment of Psychology, University of Quebec at Trois-Rivières, Trois-Rivières, Canada.ORCID http://orcid.org/0000-0002-9069-6149

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-2020-06706
6 · The paper itself

Abstract

We perceive emotions daily through facial expressions, often accompanied by a body posture that provide additional emotional context. Congruent facial and bodily expressions (conveying the same emotion) enhance emotional recognition compared to incongruent ones, suggesting interaction between these channels. Although behavioral evidence suggests that this integration occur automatic, its underlying neural mechanisms remains unclear. This study investigated the automaticity of facial and bodily expressions integration by manipulating cognitive load. Twenty-eight participants completed an emotion recognition task with congruent or incongruent facial and bodily expressions while performing a memory task under low or high cognitive load. EEG recordings captured brain activity, and emotion recognition accuracy and reaction times were measured. Results revealed that congruent expressions improved recognition, with bodily expressions exerting a stronger influence on facial expression recognition than vice versa. Early neural responses (P100, N100, P250, N250) were stronger during facial expression focus, while later responses reflected attention to body expressions. Bayesian analyses provided strong evidence for the absence of significant interaction between congruence and cognitive load, supporting the automaticity of integration. These findings suggest that emotional expressions are integrated automatically, independent of cognitive resources, and emphasize the differential influence of bodily expressions over facial expressions in shaping emotional perception.

Indexed as

CognitionEmotionsFacial ExpressionFacial RecognitionAdultBayes TheoremBrainElectroencephalographyEvoked PotentialsFemaleHumansMaleReaction TimeYoung AdultAutomaticityBodily expressionCognitive loadContextual effectFacial emotion

Identifiers

PMID40750969
PMCPMC12317001

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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.