Evidence map›Paper›PMID 30515914›Full record

ArticleHuman brain mapping2019

Tracking the dynamic functional connectivity structure of the human brain across the adult lifespan.

Yunman Xia, Qunlin Chen, Liang Shi, MengZe Li, Weikang Gong, Hong Chen, Jiang Qiu

Abstract read
In one paragraph

Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
–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

43 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Variation in high-amplitude events across the human lifespan.Network neuroscience (Cambridge, Mass.) · 2026
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  9. Dynamic Functional Connectivity Markers in Anorexia Nervosa and Their Association With Clinical Symptoms: A Cross-Sectional Study.European eating disorders review : the journal of the Eating Disorders Association · 2025
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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

7 authors.

Yunman XiaKey Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China.
Qunlin ChenKey Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China.
Liang ShiKey Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China.
MengZe LiKey Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China.
Weikang GongKey Laboratory of Computational Biology, CASMPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
Hong ChenKey Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China.
Jiang QiuKey Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China.ORCID 0000-0003-0269-5910

Funding

China Postdoctoral Science Foundation 2015M572423China Postdoctoral Science Foundation 2015M580767Chongqing Postdoctoral Science Foundation Xm2015037Chongqing Postdoctoral Science Foundation Xm2016044Fok Ying Tong Education Foundation 151023Fok Ying Tung Education Foundation 151023Fundamental Research Funds for the Central Universities SWU1509383Fundamental Research Funds for the Central Universities SWU1509451Fundamental Research Funds for the Central Universities SWU1609177Ministry of Education 14JJD880009National Natural Science Foundation of China 31470981National Natural Science Foundation of China 31500885National Natural Science Foundation of China 31571137Natural Science Foundation of Chongqing cstc2015jcyjA10106
6 · The paper itself

Abstract

The transition from early adulthood to the elder is marked by functional and structural brain transformations. Many previous studies examined the correlation between the functional connectivity (FC) and aging using resting-state fMRI. Results showed that the changes in FC are linked to aging as well as the cognitive ability changes. However, some researchers proposed that the FC is not static but dynamic changes during the resting-state fMRI scan. In this study, we examined the correlation between the resting-state dynamic functional network connectivity and age using resting scan data of 434 subjects. The results suggested: (a) age is negatively associated with variability of dynamic functional network connectivity state; (b) the dwell time of each age range spends in each state is different; (c) the dynamic graph metrics curve of each age ranges is different and 19-30 age range has the largest average global efficiency and average local efficiency; (d) some dynamic functional network connectivity measures were correlated to the certain cognitive ability. Overall, the results suggested the changes in dynamic functional network connectivity measures may be a characteristic of the aging process and in further investigations may provide a deep understanding of the aging process.

Indexed as

AdultAgedAged, 80 and overAgingBrainBrain MappingFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeural PathwaysYoung Adultagingdynamic functional network connectivitygraph theoryWechsler adult intelligence scale

Identifiers

PMID30515914
PMCPMC6865727

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.