Evidence map›Paper›PMID 41457128›Full record

ArticleAttention, perception & psychophysics2025

Lateralized costs of divided attention to faces.

Samantha C Lee, Lars Strother

Abstract read
In one paragraph

Article in Attention, perception & psychophysics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Samantha C LeeDepartment of Psychology at the University of Nevada, Reno, 1664 N. Virginia St, Reno, NV, 89557, USA. samanthalee@unr.edu.ORCID http://orcid.org/0000-0001-5164-7523
Lars StrotherDepartment of Psychology at the University of Nevada, Reno, 1664 N. Virginia St, Reno, NV, 89557, USA.

Funding

Virtual Reality and Augmented Reality CoreP20GM103650 · NIGMS · UNIVERSITY OF NEVADA RENO · PI WEBSTER, MICHAEL A · 2012 to 2022
$20.9M
Virtual and Augmented Reality Interaction CoreP30GM145646 · NIGMS · UNIVERSITY OF NEVADA RENO · PI MICHAEL A WEBSTER · 2022 to 2026
$6.8M
NIGMS NIH HHS P20 GM103650NIGMS NIH HHS P30 GM145646
6 · The paper itself

Abstract

We used a dual-task paradigm to study the relationship between lateralized face perception and attention by measuring the costs of dividing attention between faces viewed in opposite visual fields. Observers performed judgments of either the sex, orientation, or color of one (single-task, cued) or both (dual-task, uncued) faces in a tachistoscopically viewed pair. We observed dual-task costs (i.e., decreased accuracy for dual- relative to single-task performance) for categorical judgments of face sex (female/male) and orientation (upright/inverted), both of which necessitated visual processing of face-specific information. We did not observe costs for judgments of face color (red-tinted/greyscale), which could be performed without processing face-specific visual information per se. We also observed an unexpected "feature contrast" effect of category-incongruency for judgments of face sex, such that observers showed no dual-task cost when faces in a pair belonged to opposite categories (e.g., female/male) as compared with the same category (e.g., female/female). Finally, dual-task costs for judgments of face sex and orientation (but not color) showed a left visual field (LVF) advantage: dual-task costs were greater in the right visual field (RVF) than in the LVF. We interpret this LVF cost advantage for judgments of face sex and orientation as indicative of the type of visual processing needed to perform face-based judgments. Our results show, for the first time, that the LVF advantage in face perception is directly related to capacity limits induced by divided attention to faces.

Indexed as

AttentionFacial RecognitionFunctional LateralityPattern Recognition, VisualAdultColor PerceptionCuesFemaleHumansJudgmentMaleOrientationReaction TimeVisual FieldsYoung AdultDivided attentionDual-taskFace perceptionFace sexLateralityLVF advantage

Identifiers

PMID41457128
PMCPMC12745327

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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.