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身体机能与感觉运动网络和背侧注意网络连通性的关联:为什么检查身体机能的特定组成部分很重要。

Association of physical function with connectivity in the sensorimotor and dorsal attention networks: why examining specific components of physical function matters.

机构信息

Department of Radiology, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA.

Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

出版信息

Geroscience. 2024 Oct;46(5):4987-5002. doi: 10.1007/s11357-024-01251-8. Epub 2024 Jul 5.

Abstract

Declining physical function with aging is associated with structural and functional brain network organization. Gaining a greater understanding of network associations may be useful for targeting interventions that are designed to slow or prevent such decline. Our previous work demonstrated that the Short Physical Performance Battery (eSPPB) score and body mass index (BMI) exhibited a statistical interaction in their associations with connectivity in the sensorimotor cortex (SMN) and the dorsal attention network (DAN). The current study examined if components of the eSPPB have unique associations with these brain networks. Functional magnetic resonance imaging was performed on 192 participants in the BNET study, a longitudinal and observational trial of community-dwelling adults aged 70 or older. Functional brain networks were generated for resting state and during a motor imagery task. Regression analyses were performed between eSPPB component scores (gait speed, complex gait speed, static balance, and lower extremity strength) and BMI with SMN and DAN connectivity. Gait speed, complex gait speed, and lower extremity strength significantly interacted with BMI in their association with SMN at rest. Gait speed and complex gait speed were interacted with BMI in the DAN at rest while complex gait speed, static balance, and lower extremity strength interacted with BMI in the DAN during motor imagery. Results demonstrate that different components of physical function, such as balance or gait speed and BMI, are associated with unique aspects of brain network organization. Gaining a greater mechanistic understanding of the associations between low physical function, body mass, and brain physiology may lead to the development of treatments that not only target specific physical function limitations but also specific brain networks.

摘要

随着年龄的增长,身体功能的下降与大脑结构和功能网络组织有关。更深入地了解网络关联可能有助于针对旨在减缓或预防这种下降的干预措施。我们之前的工作表明,简易体能状况量表 (Short Physical Performance Battery, eSPPB) 评分和体重指数 (body mass index, BMI) 在与感觉运动皮层 (sensorimotor cortex, SMN) 和背侧注意网络 (dorsal attention network, DAN) 的连通性相关联时存在统计学上的相互作用。本研究探讨了 eSPPB 的组成部分是否与这些大脑网络具有独特的关联。在 BNET 研究中对 192 名 70 岁或以上的社区居住成年人进行了功能磁共振成像。为静息状态和运动想象任务生成了功能大脑网络。在静息状态下,对 eSPPB 组成部分(步态速度、复杂步态速度、静态平衡和下肢力量)与 SMN 和 DAN 连通性之间的 BMI 进行回归分析。步态速度、复杂步态速度和下肢力量与 SMN 之间的关联与 BMI 显著相互作用。在静息状态下,步态速度和复杂步态速度与 BMI 相互作用,而复杂步态速度、静态平衡和下肢力量与运动想象期间的 DAN 与 BMI 相互作用。结果表明,不同的身体功能成分,如平衡或步态速度和 BMI,与大脑网络组织的独特方面相关联。更深入地了解低身体功能、体重和大脑生理学之间的关联的机制,可能会导致不仅针对特定身体功能限制而且针对特定大脑网络的治疗方法的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ad2/11336134/9552f32ff660/11357_2024_1251_Fig1_HTML.jpg

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