Evidence map›Paper›PMID 38102475›Full record

ArticleSocial cognitive and affective neuroscience2024

The speed of race.

Peter de Lissa, Pauline Schaller, Roberto Caldara

Abstract read
In one paragraph

Article in Social cognitive and affective neuroscience, 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

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

3 citing papers in PubMed.

  1. Frequency-tagged EEG reveals category-selective responses to face race.Social cognitive and affective neuroscience · 2026
    Article
  2. Article
  3. 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

3 authors.

Peter de LissaEye and Brain Mapping Laboratory (iBMLab), Department of Psychology, University of Fribourg, Fribourg 1700, Switzerland.ORCID 0000-0003-3596-5075
Pauline SchallerEye and Brain Mapping Laboratory (iBMLab), Department of Psychology, University of Fribourg, Fribourg 1700, Switzerland.ORCID 0000-0001-8747-1769
Roberto CaldaraEye and Brain Mapping Laboratory (iBMLab), Department of Psychology, University of Fribourg, Fribourg 1700, Switzerland.ORCID 0000-0002-8260-9949

Funding

Swiss National Science Foundation 100019_189018
6 · The paper itself

Abstract

When asked to categorize faces according to 'race', people typically categorize other-race faces faster than faces belonging to their own race. This 'Other Race Categorization Advantage' is thought to reflect enhanced sensitivity to early visual signals characteristic of other-race faces, and can manifest within 200 ms of face presentation. However, recent research has highlighted the importance of signal intensity in this effect, where visual-degradation of the face images significantly enhances the effect and exposes a behavioural threshold at very low levels of visual quality where other-race visual signals are able to be perceived while same-race signals are not. The current study investigated the effect of signal intensity in race categorization processes in the brain through electroencephalography and in accuracy/reaction times. While replicating the previously observed enhancement of the other-race categorization advantage, we also found enhanced sensitivity to other-race faces in early P1 peaks, as well as later N170 and N250 peaks. These effects, however, related to the varying levels of signal intensity in the face stimuli, suggesting that race categorization may involve different types of perceptual and neural processes rather than one discrete process. The speed at which race is perceived depends on the intensity of the face signal.

Indexed as

FacePattern Recognition, VisualBrainElectroencephalographyHumansPhotic Stimulationface processingN170other-race face categorization advantageP1race

Identifiers

PMID38102475
PMCPMC10868132

What OpenQuestion holds

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LicenceCC BY
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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.