Evidence map›Paper›PMID 37244937›Full record

ArticleScientific reports2023

Horses (Equus caballus) facial micro-expressions: insight into discreet social information.

Claude Tomberg, Maxime Petagna, Lucy-Anne de Selliers de Moranville

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Claude TombergFaculty of Medicine, Université Libre de Bruxelles, 808, Route de Lennik, CP 630, 1070, Brussels, Belgium. ctomberg@ulb.ac.be.
Maxime PetagnaFaculty of Medicine, Université Libre de Bruxelles, 808, Route de Lennik, CP 630, 1070, Brussels, Belgium.
Lucy-Anne de Selliers de MoranvilleFaculty of Medicine, Université Libre de Bruxelles, 808, Route de Lennik, CP 630, 1070, Brussels, Belgium.
Université Libre de Bruxelles · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Facial micro-expressions are facial expressions expressed briefly (less than 500 ms) and involuntarily. Described only in humans, we investigated whether micro-expressions could also be expressed by non-human animal species. Using the Equine Facial action coding system (EquiFACS), an objective tool based on facial muscles actions, we demonstrated that a non-human species, Equus caballus, is expressing facial micro-expressions in a social context. The AU17, AD38 and AD1 were selectively modulated as micro-expression-but not as standard facial expression (all durations included)-in presence of a human experimenter. As standard facial expressions, they have been associated with pain or stress but our results didn't support this association for micro-expressions which may convey other information. Like in humans, neural mechanisms underlying the exhibit of micro-expressions may differ from those of standard facial expressions. We found that some micro-expressions could be related to attention and involved in the multisensory processing of the 'fixed attention' observed in horses' high attentional state. The micro-expressions could be used by horses as social information in an interspecies relationship. We hypothesize that facial micro-expressions could be a window on transient internal states of the animal and may provide subtle and discreet social signals.

Indexed as

FaceFacial ExpressionAnimalsFacial MusclesHorsesHumansPainSocial Environment

Identifiers

PMID37244937
PMCPMC10224940
OpenAlexW4378530789

What OpenQuestion holds

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LicenceCC BY
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.