Evidence map›Paper›PMID 31907838›Full record

ArticleAttention, perception & psychophysics2020

Rapid and coarse face detection: With a lack of evidence for a nasal-temporal asymmetry.

Laura Cabral, Bobby Stojanoski, Rhodri Cusack

Abstract read
In one paragraph

Article in Attention, perception & psychophysics, 2020. 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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.

Laura CabralBrain and Mind Institute, Western University, London, ON, N6A 5B7, Canada. lcabral@uwo.ca.
Bobby StojanoskiBrain and Mind Institute, Western University, London, ON, N6A 5B7, Canada.
Rhodri CusackBrain and Mind Institute, Western University, London, ON, N6A 5B7, Canada.

Funding

Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant 418293DG-2012Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grat 418293DG-2012
6 · The paper itself

Abstract

Humans have structures dedicated to the processing of faces, which include cortical components (e.g., areas in occipital and temporal lobes) and subcortical components (e.g., superior colliculus and amygdala). Although faces are processed more quickly than stimuli from other categories, there is a lack of consensus regarding whether subcortical structures are responsible for rapid face processing. In order to probe this, we exploited the asymmetry in the strength of projections to subcortical structures between the nasal and temporal hemiretina. Participants detected faces from unrecognizable control stimuli and performed the same task for houses. In Experiments 1 and 3, at the fastest reaction times, participants detected faces more accurately than houses. However, there was no benefit of presenting to the subcortical pathway. In Experiment 2, we probed the coarseness of the rapid pathway, making the foil stimuli more similar to faces and houses. This eliminated the rapid detection advantage, suggesting that rapid face processing is limited to coarse representations. In Experiment 4, we sought to determine whether the natural difference between spatial frequencies of faces and houses were driving the effects seen in Experiments 1 and 3. We spatially filtered the faces and houses so that they were matched. Better rapid detection was again found for faces relative to houses, but we found no benefit of preferentially presenting to the subcortical pathway. Taken together, the results of our experiments suggest a coarse rapid detection mechanism, which was not dependent on spatial frequency, with no advantage for presenting preferentially to subcortical structures.

Indexed as

AdolescentAdultAmygdalaFacial AsymmetryFacial RecognitionFemaleHumansMalePattern Recognition, VisualPhotic StimulationReaction TimeYoung AdultFace detectionNasal temporal asymmetryRapid processingRetinocollicular pathwaySubcortical

Identifiers

PMID31907838
PMCPMC7297860

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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.