Dual-functional stability (DFS) in cognitive and physical abilities is important for successful aging. This study examines the brain topology profiles that underpin high DFS in older adults by testing two hypotheses: (1) older adults with high DFS would exhibit a unique brain organization that preserves their physical and cognitive functions across various tasks, and (2) any individuals with this distinct brain topology would consistently show high DFS. We analyzed two cohorts of cognitively and physically healthy older adults from the UK (Cam-CAN, n = 79) and the US (CF, n = 48) using neuroimaging data and a combination of cognitive and physical tasks. Variability in DFS was characterized using k-mean clustering for intra-individual variability (IIV) in cognitive and physical tasks. Graph theory analyses of diffusion tensor imaging connectomes were used to assess brain network segregation and integration through clustering coefficients (CCs) and shortest path lengths (PLs). Using support vector machine and regression, brain topology features, derived from PLs + CCs, differentiated the high DFS subgroup from low and mix DFS subgroups with accuracies of 65.82% and 84.78% in Cam-CAN and CF samples, respectively, which predicted cross-task DFS score in CF samples at 58.06% and 70.53% for cognitive and physical stability, respectively. Results showed distinctive neural correlates associated with high DFS, notably varying regional brain segregation and integration within critical areas such as the insula, frontal pole, and temporal pole. The identified brain topology profiles suggest a distinctive neural basis for DFS, a trait indicative of successful aging. These insights offer a foundation for future research to explore targeted interventions that could enhance cognitive and physical resilience in older adults, promoting a healthier and more functional lifespan.

认知和身体能力的双重功能稳定性 （DFS） 对于成功老龄化很重要。本研究通过检验两个假设来检查支撑老年人高 DFS 的大脑拓扑概况：（1） 具有高 DFS 的老年人会表现出独特的大脑组织，在各种任务中保留他们的身体和认知功能，以及 （2） 任何具有这种独特大脑拓扑结构的个体都会始终表现出高 DFS。我们使用神经影像学数据以及认知和身体任务的组合分析了来自英国 （Cam-CAN， n = 79） 和美国 （CF， n = 48） 的两组认知和身体健康的老年人。使用认知和体力任务中个体内变异性 （IIV） 的 k 均值聚类来表征 DFS 的变异性。扩散张量成像连接组的图论分析用于通过聚类系数 （CC） 和最短路径长度 （PLs） 评估脑网络分离和整合。利用支持向量机和回归，源自 PLs + CCs 的脑拓扑特征将高 DFS 亚组与低和混合 DFS 亚组区分开来，在 Cam-CAN 和 CF 样本中的准确率分别为 65.82% 和 84.78%，预测 CF 样本的认知和身体稳定性跨任务 DFS 评分分别为 58.06% 和 70.53%。结果显示与高 DFS 相关的独特神经相关性，显着改变关键区域（如岛叶、额极和颞极）内的区域性大脑分离和整合。确定的大脑拓扑图谱表明 DFS 具有独特的神经基础，这是表明成功衰老的特征。 这些见解为未来的研究提供了基础，以探索可以增强老年人认知和身体弹性的针对性干预措施，促进更健康、更实用的寿命。