Evidence map›Paper›PMID 38137147›Full record

ArticleBrain sciences2023

The Impact of Spatial Frequency on the Perception of Crowd Emotion: An fMRI Study.

Dongfang Zhao, Xiangnan Shen, Shuaixia Li, Weiqi He

Abstract read
In one paragraph

Article in Brain sciences, 2023. 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

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

2 citing papers in PubMed.

  1. Article
  2. Review
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

4 authors.

Dongfang ZhaoResearch Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.
Xiangnan ShenResearch Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.
Shuaixia LiResearch Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.ORCID 0000-0002-2971-1426
Weiqi HeResearch Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.

Funding

atural Science Foundation of Liaoning Province 2023-MS-252Liaoning Revitalization Talents Program XLYC2007106National Natural Science Foundation of China 31970991
6 · The paper itself

Abstract

Recognizing the emotions of faces in a crowd is crucial for understanding overall behavior and intention as well as for smooth and friendly social interactions. However, it is unclear whether the spatial frequency of faces affects the discrimination of crowd emotion. Although high- and low-spatial-frequency information for individual faces is processed by distinct neural channels, there is a lack of evidence on how this applies to crowd faces. Here, we used functional magnetic resonance imaging (fMRI) to investigate neural representations of crowd faces at different spatial frequencies. Thirty-three participants were asked to compare whether a test face was happy or more fearful than a crowd face that varied in high, low, and broad spatial frequencies. Our findings revealed that fearful faces with low spatial frequencies were easier to recognize in terms of accuracy (78.9%) and response time (927 ms). Brain regions, such as the fusiform gyrus, located in the ventral visual stream, were preferentially activated in high spatial frequency crowds, which, however, were the most difficult to recognize behaviorally (68.9%). Finally, the right inferior frontal gyrus was found to be better activated in the broad spatial frequency crowds. Our study suggests that people are more sensitive to fearful crowd faces with low spatial frequency and that high spatial frequency does not promote crowd face recognition.

Indexed as

crowd emotioncrowd facesensemble codingfMRIspatial frequency

Identifiers

PMID38137147
PMCPMC10742193

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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.