Evidence map›Paper›PMID 31281246›Full record

ArticleFrontiers in human neuroscience2019

The Neural Correlate Difference Between Positive and Negative Awe.

Fang Guan, Sasa Zhao, Shaona Chen, Shi Lu, Jun Chen, Yanhui Xiang

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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

6 authors.

Fang GuanSchool of Psychology and Center for Study of Applied Psychology, South China Normal University, Guangzhou, China.
Sasa ZhaoUMR 5229, Institut des Sciences Cognitives Marc Jeannerod, CNRS, Université Claude Bernard Lyon 1, Lyon, France.
Shaona ChenSchool of Psychology and Center for Study of Applied Psychology, South China Normal University, Guangzhou, China.
Shi LuDepartment of Psychology, University of Washington, Seattle, WA, USA.
Jun ChenSchool of Psychology and Center for Study of Applied Psychology, South China Normal University, Guangzhou, China.
Yanhui XiangDepartment of Psychology, Hunan Normal University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Awe is an emotional response to perceptually vast stimuli that transcend current frames of reference. Narrative and experimental work has characterized two distinct variants of awe: positive and negative; however, little is known about the structural neural basis associated with the differences of these two variants of awe. In this study, we investigated the structural neural basis of positive and negative awe underlying individual differences among 62 young healthy adults. Specifically, we assessed the association between regional gray matter volume (rGMV) and the two different variants of awe using the voxel-based morphometry (VBM). A partial correlation analysis was conducted to examine the relationship between rGMV and behavioral positive and negative awe, while controlling for sex, age and total GMV. VBM indicated that positive awe was positively correlated with GMV in the precuneus, and negatively correlated with GMV in the left fusiform and the right calcarine. Negative awe was negatively correlated with GMV in the left and right insula, and the left superior temporal gyrus. These results provide a neural explanation for the differences of these two variants of awe.

Indexed as

insulanegative awepositive aweprecuneusvoxel-based morphometry

Identifiers

PMID31281246
PMCPMC6597956

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.