Identification of key brain networks and functional connectivities of successful aging: A surface-based resting-state functional magnetic resonance study.

IF 3.9 4区 医学 Q1 PSYCHIATRY
Jiao-Jiao Sun, Li Zhang, Ru-Hong Sun, Xue-Zheng Gao, Chun-Xia Fang, Zhen-He Zhou
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Abstract

Background: Successful aging (SA) refers to the ability to maintain high levels of physical, cognitive, psychological, and social engagement in old age, with high cognitive function being the key to achieving SA.

Aim: To explore the potential characteristics of the brain network and functional connectivity (FC) of SA.

Methods: Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly, which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination (MMSE). The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf, and the brain functional network was conducted by DPABINet. The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.

Results: The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance. The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score, and the FC of the right supramarginal gyrus and right temporal pole: Middle temporal gyrus was the only one decreased and negatively related to MMSE score. All 17 significantly altered FCs of SA were taken into the support vector machine model, and the area under the curve was 0.895.

Conclusion: The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.

成功衰老的关键脑网络和功能连接的识别:基于表面静息状态的功能磁共振研究。
背景:成功老龄化(SA)是指在老年时期保持高水平的身体、认知、心理和社会参与的能力,而高水平的认知功能是实现成功老龄化的关键。目的:探讨SA脑网络和功能连通性的潜在特征。方法:从社区居住老年人中招募SA个体26例和正常老年人47例,进行磁共振成像扫描和Mini Mental State Examination (MMSE)整体认知功能评估。静息状态-功能磁共振成像数据采用DPABISurf预处理,脑功能网络采用DPABINet进行。通过改变功能连接度,构建支持向量机模型来评价SA的识别价值。结果:结果发现,5个脑网络的6个网络间fc发生显著改变,并与MMSE表现相关。额中回右眶部和右角回FC多升高,与MMSE评分呈正相关,右边缘上回和右颞极颞中回FC下降,与MMSE评分负相关。将17个SA显著改变的fc全部纳入支持向量机模型,曲线下面积为0.895。结论:确定SA的关键脑网络和FC有助于我们更好地了解SA的脑机制,并进一步探索SA的神经影像学生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
6.50%
发文量
110
期刊介绍: The World Journal of Psychiatry (WJP) is a high-quality, peer reviewed, open-access journal. The primary task of WJP is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of psychiatry. In order to promote productive academic communication, the peer review process for the WJP is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJP are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in psychiatry.
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