Age-Related Changes in Brain Network Modularity Based on the Dynamic Sliding-Window Subnetwork Voting Method

IF 1.7 4区医学 Q3 DEVELOPMENTAL BIOLOGY

International Journal of Developmental Neuroscience Pub Date : 2025-06-03 DOI:10.1002/jdn.70025

Jianxi Liu, Nannan Xia, Kang Hu, Mingcong Huang, Zeqiang Linli

{"title":"Age-Related Changes in Brain Network Modularity Based on the Dynamic Sliding-Window Subnetwork Voting Method","authors":"Jianxi Liu, Nannan Xia, Kang Hu, Mingcong Huang, Zeqiang Linli","doi":"10.1002/jdn.70025","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background and Purpose</h3>\n \n <p>An understanding of the modular structure of brain functional networks and their changes with age is beneficial in uncovering the neural mechanisms that underlie cognitive decline during the ageing process. Compared to simpler networks, such as social networks, the execution of brain functions always depends on extensive interactions among multiple brain regions, which complicates the detection of accurate, stable and physiologically meaningful community structures. However, although previous work has focused on the modular organization of the brain, there has been insufficient research on its specific dynamic changes and how these evolve with age. In this case, this paper investigates the modular structure of human brain functional networks and their dynamic changes across different age groups, revealing the impact of ageing on brain network functionality.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Firstly, we constructed brain networks using a dynamic sliding-window subnetwork voting method. Further, this paper, based on public datasets and the Girvan–Newman (GN) community detection algorithm, effectively divided the community structure of brain networks and calculated modularity. It focused on analysing the brain network characteristics of 439 participants under rs-fMRI data.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The results of the variance analysis indicate significant differences in modularity across different age groups. The brain networks of younger participants exhibited pronounced modular characteristics and higher efficiency in information processing. In contrast, older participants displayed a significant reduction in modularity, reflecting a trend towards functional integration.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>These changes are closely related to the decline in cognitive abilities and the degeneration of neural connections.</p>\n </section>\n </div>","PeriodicalId":13914,"journal":{"name":"International Journal of Developmental Neuroscience","volume":"85 4","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Developmental Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jdn.70025","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEVELOPMENTAL BIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background and Purpose

An understanding of the modular structure of brain functional networks and their changes with age is beneficial in uncovering the neural mechanisms that underlie cognitive decline during the ageing process. Compared to simpler networks, such as social networks, the execution of brain functions always depends on extensive interactions among multiple brain regions, which complicates the detection of accurate, stable and physiologically meaningful community structures. However, although previous work has focused on the modular organization of the brain, there has been insufficient research on its specific dynamic changes and how these evolve with age. In this case, this paper investigates the modular structure of human brain functional networks and their dynamic changes across different age groups, revealing the impact of ageing on brain network functionality.

Methods

Firstly, we constructed brain networks using a dynamic sliding-window subnetwork voting method. Further, this paper, based on public datasets and the Girvan–Newman (GN) community detection algorithm, effectively divided the community structure of brain networks and calculated modularity. It focused on analysing the brain network characteristics of 439 participants under rs-fMRI data.

Results

The results of the variance analysis indicate significant differences in modularity across different age groups. The brain networks of younger participants exhibited pronounced modular characteristics and higher efficiency in information processing. In contrast, older participants displayed a significant reduction in modularity, reflecting a trend towards functional integration.

Conclusion

These changes are closely related to the decline in cognitive abilities and the degeneration of neural connections.

查看原文本刊更多论文

基于动态滑动窗口子网络投票方法的脑网络模块化年龄相关变化

背景与目的了解脑功能网络的模块化结构及其随年龄的变化，有助于揭示衰老过程中认知能力下降的神经机制。与社会网络等更简单的网络相比，大脑功能的执行总是依赖于多个大脑区域之间的广泛相互作用，这使得准确、稳定和生理上有意义的社区结构的检测变得复杂。然而，尽管以前的工作主要集中在大脑的模块化组织上，但对其具体的动态变化以及这些变化如何随着年龄的增长而演变的研究还不够。在这种情况下，本文研究了人类大脑功能网络的模块化结构及其在不同年龄段的动态变化，揭示了老龄化对大脑网络功能的影响。方法首先，采用动态滑动窗口子网络投票方法构建脑网络；在此基础上，基于公共数据集和GN （Girvan-Newman）社区检测算法，对脑网络的社区结构进行了有效的划分，并计算了模块性。重点分析了439名参与者在rs-fMRI数据下的大脑网络特征。结果方差分析结果显示，不同年龄组的模块性存在显著差异。年轻参与者的大脑网络表现出明显的模块化特征和更高的信息处理效率。相比之下，年龄较大的参与者显示出模块性的显著降低，反映出功能整合的趋势。结论这些变化与认知能力下降和神经连接变性密切相关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Developmental Neuroscience 医学-发育生物学

CiteScore

3.30

自引率

5.60%

发文量

审稿时长

6-12 weeks

期刊介绍： International Journal of Developmental Neuroscience publishes original research articles and critical review papers on all fundamental and clinical aspects of nervous system development, renewal and regeneration, as well as on the effects of genetic and environmental perturbations of brain development and homeostasis leading to neurodevelopmental disorders and neurological conditions. Studies describing the involvement of stem cells in nervous system maintenance and disease (including brain tumours), stem cell-based approaches for the investigation of neurodegenerative diseases, roles of neuroinflammation in development and disease, and neuroevolution are also encouraged. Investigations using molecular, cellular, physiological, genetic and epigenetic approaches in model systems ranging from simple invertebrates to human iPSC-based 2D and 3D models are encouraged, as are studies using experimental models that provide behavioural or evolutionary insights. The journal also publishes Special Issues dealing with topics at the cutting edge of research edited by Guest Editors appointed by the Editor in Chief. A major aim of the journal is to facilitate the transfer of fundamental studies of nervous system development, maintenance, and disease to clinical applications. The journal thus intends to disseminate valuable information for both biologists and physicians. International Journal of Developmental Neuroscience is owned and supported by The International Society for Developmental Neuroscience (ISDN), an organization of scientists interested in advancing developmental neuroscience research in the broadest sense.