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.

随着年龄的增长，身体机能下降与大脑网络组织的结构和功能有关。更好地了解网络关联可能有助于制定旨在减缓或防止这种下降的干预措施。我们之前的工作表明，短期身体表现电池（eSPPB）评分和体重指数（BMI）与感觉运动皮层（SMN）和背侧注意力网络（DAN）的连接性之间存在统计交互作用。当前的研究检查了 eSPPB 的组成部分是否与这些大脑网络有独特的关联。 BNET 研究对 192 名参与者进行了功能性磁共振成像，这是一项针对 70 岁或以上社区居民的纵向观察性试验。功能性大脑网络是在静息状态和运动想象任务期间生成的。在 eSPPB 组成分数（步态速度、复杂步态速度、静态平衡和下肢力量）和 BMI 以及 SMN 和 DAN 连接之间进行回归分析。步态速度、复杂步态速度和下肢力量与 BMI 和静息时 SMN 之间存在显着的交互作用。静息时，步态速度和复杂步态速度与 DAN 中的 BMI 相互作用，而运动想象期间，复杂步态速度、静态平衡和下肢力量与 DAN 中的 BMI 相互作用。结果表明，身体功能的不同组成部分，例如平衡或步态速度和体重指数，与大脑网络组织的独特方面相关。 对身体机能低下、体重和大脑生理学之间的关联获得更深入的机制理解可能会导致开发出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。