Evidence map›Paper›PMID 37954936›Full record

ArticleFrontiers in human neuroscience2023

Face processing and early event-related potentials: replications and novel findings.

Nicolas M Brunet

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

1 author.

Nicolas M BrunetDepartment of Psychology, California State University of San Bernardino, San Bernardino, CA, United States.

Funding

Improving the reliability of eye tracking to diagnose concussion.R15NS121788 · NINDS · MILLSAPS COLLEGE · PI BRUNET, NICOLAS M · 2021 to 2021
$396k
NINDS NIH HHS R15 NS121788
6 · The paper itself

Abstract

This research explores early Event-Related Potentials (ERPs) sensitivity to facial stimuli, investigating various facial features aimed to unveil underlying neural mechanisms. Two experiments, each involving 15 undergraduate students, utilized a multidimensional stimulus set incorporating race, gender, age, emotional expression, face masks, and stimulus orientation. Findings highlight significant modulations in N170 and P200 amplitudes and latencies for specific attributes, replicating prior research and revealing novel insights. Notably, age-related facial feature variations, facial inversion, and the presence of face masks significantly impact neural responses. Several speculative explanations are proposed to elucidate these results: First, the findings lend support to the idea that the increased N170 amplitude observed with facial inversion is closely tied to the activation of object-sensitive neurons. This is further bolstered by a similar amplitude increase noted when masks (effective objects) are added to faces. Second, the absence of an additional amplitude increase, when inverting face images with face masks suggests that neural populations may have reached a saturation point, limiting further enhancement. Third, the study reveals that the latency deficit in N170 induced by facial inversion is even more pronounced in the subsequent ERP component, the P200, indicating that face inversion may impact multiple stages of face processing. Lastly, the significant increase in P200 amplitude, typically associated with face typicality, for masked faces in this study aligns with previous research that demonstrated elevated P200 amplitudes for scrambled faces. This suggests that obscured faces may be processed as typical, potentially representing a default state in face processing.

Indexed as

ageamplitudeEEGERPface inversionface maskN170P200

Identifiers

PMID37954936
PMCPMC10634455

What OpenQuestion holds

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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.