Evidence map›Paper›PMID 39297127›Full record

ArticleIBRO neuroscience reports2024

Age-related changes of node degree in the multiple-demand network predict fluid intelligence.

Lizhi Yu, Qin Zhang, Xiaoyang Li, Mei Zhang, Xiaolin Chen, Mingchun Lu, Zhen Ouyang

Abstract read
In one paragraph

Article in IBRO neuroscience reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Lizhi YuDepartment of Radiology, Taian Municipal Hospital, Taian, Shandong, China.
Qin ZhangDepartment of Radiology, Taian Municipal Hospital, Taian, Shandong, China.
Xiaoyang LiDepartment of Radiology, Taian Municipal Hospital, Taian, Shandong, China.
Mei ZhangDepartment of Radiology, Taian Municipal Hospital, Taian, Shandong, China.
Xiaolin ChenPhysical examination department, Taian Municipal Hospital, Taian, Shandong, China.
Mingchun LuDepartment of Radiology, Taian Municipal Hospital, Taian, Shandong, China.
Zhen OuyangDepartment of Radiology, Taian Municipal Hospital, Taian, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fluid intelligence is an individual's innate ability to cope with complex situations and is gradually reduced across adults aging. The realization of fluid intelligence requires the simultaneous activity of multiple brain regions and depends on the structural connection of distributed brain regions. Uncovering the structural features of brain connections associated with fluid intelligence decline will provide reference for the development of intervention and treatment programs for cognitive decline. Using structural magnetic resonance imaging data of 454 healthy participants (18-87 years) from the Cam-CAN dataset, we constructed structural similarity network for each participant and calculated the node degree. Spearman correlation analysis showed that age was positively correlated with degree centrality in the cingulate cortex, left insula and subcortical regions, while negatively correlated with that in the orbito-frontal cortex, right middle temporal and precentral regions. Partial least squares (PLS) regression showed that the first PLS components explained 32 % (second PLS component: 20 %,

Indexed as

AgingFluid intelligenceMultiple-demand networkNodal degreeSMRI

Identifiers

PMID39297127
PMCPMC11409069

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.