Evidence map›Paper›PMID 27065927›Full record

ArticleFrontiers in psychology2016

Automatic Change Detection to Facial Expressions in Adolescents: Evidence from Visual Mismatch Negativity Responses.

Tongran Liu, Tong Xiao, Jiannong Shi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 24 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 3 institutions in 2 countries.

Tongran LiuKey Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences Beijing, China.
Tong XiaoNatural Language Processing Laboratory, College of Information Science and Engineering, Northeastern University Liaoning, China.
Jiannong ShiKey Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of SciencesBeijing, China; Department of Learning and Philosophy, Aalborg UniversityAalborg, Denmark.
Institute of Physics · CNInstitute of Psychology, Chinese Academy of Sciences · CNNortheastern University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adolescence is a critical period for the neurodevelopment of social-emotional processing, wherein the automatic detection of changes in facial expressions is crucial for the development of interpersonal communication. Two groups of participants (an adolescent group and an adult group) were recruited to complete an emotional oddball task featuring on happy and one fearful condition. The measurement of event-related potential was carried out via electroencephalography and electrooculography recording, to detect visual mismatch negativity (vMMN) with regard to the automatic detection of changes in facial expressions between the two age groups. The current findings demonstrated that the adolescent group featured more negative vMMN amplitudes than the adult group in the fronto-central region during the 120-200 ms interval. During the time window of 370-450 ms, only the adult group showed better automatic processing on fearful faces than happy faces. The present study indicated that adolescent's posses stronger automatic detection of changes in emotional expression relative to adults, and sheds light on the neurodevelopment of automatic processes concerning social-emotional information.

Indexed as

adolescenceautomatic change detectionERPsfacial expression perceptionvisual mismatch negativity

Identifiers

PMID27065927
PMCPMC4811878
OpenAlexW2331686490

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.