Evidence map›Paper›PMID 37578334›Full record

ArticleHuman brain mapping2023

Single-subject cortical morphological brain networks across the adult lifespan.

Jingxuan Ruan, Ningkai Wang, Junle Li, Jing Wang, Qihong Zou, Yating Lv, Han Zhang, Jinhui Wang

Abstract read
In one paragraph

Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

17 citing papers in PubMed.

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  12. Brain connectome from neuronal morphology.Network neuroscience (Cambridge, Mass.) · 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

8 authors.

Jingxuan RuanSchool of Electronics and Information Technology, South China Normal University, Foshan, China.ORCID 0000-0003-4900-3184
Ningkai WangInstitute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.ORCID 0000-0002-2363-9021
Junle LiInstitute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.
Jing WangInstitute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.
Qihong ZouCenter for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.ORCID 0000-0001-8732-6633
Yating LvInstitute of Psychological Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China.
Han ZhangSchool of Electronics and Information Technology, South China Normal University, Foshan, China.
Jinhui WangInstitute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Age-related changes in focal cortical morphology have been well documented in previous literature; however, how interregional coordination patterns of the focal cortical morphology reorganize with advancing age is not well established. In this study, we performed a comprehensive analysis of the topological changes in single-subject morphological brain networks across the adult lifespan. Specifically, we constructed four types of single-subject morphological brain networks for 650 participants (aged from 18 to 88 years old), and characterized their topological organization using graph-based network measures. Age-related changes in the network measures were examined via linear, quadratic, and cubic models. We found profound age-related changes in global small-world attributes and efficiency, local nodal centralities, and interregional similarities of the single-subject morphological brain networks. The age-related changes were mainly embodied in cortical thickness networks, involved in frontal regions and highly connected hubs, concentrated on short-range connections, characterized by linear changes, and susceptible to connections between limbic, frontoparietal, and ventral attention networks. Intriguingly, nonlinear (i.e., quadratic or cubic) age-related changes were frequently found in the insula and limbic regions, and age-related cubic changes preferred long-range morphological connections. Finally, we demonstrated that the morphological similarity in cortical thickness between two frontal regions mediated the relationship between age and cognition measured by Cattell scores. Taken together, these findings deepen our understanding of adaptive changes of the human brain with advancing age, which may account for interindividual variations in behaviors and cognition.

Indexed as

LongevityMagnetic Resonance ImagingAdolescentAdultAgedAged, 80 and overBrainBrain MappingCognitionHumansMiddle AgedYoung Adultanatomical distancehublifespanmorphological brain networkstructural MRI

Identifiers

PMID37578334
PMCPMC10543107

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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.