The intrinsic brain functional network organization continuously changes with aging. By integrating spatial and temporal information, the process of how brain networks temporally reconfigure and remain well-organized spatial structure largely reflects the brain function, thereby holds the potential to capture its age-related declines. In this study, we examined the spatiotemporal brain dynamics from resting-state functional Magnetic Resonance Imaging (fMRI) data of healthy young and older adults using a Hidden Markov Model (HMM). Six brain states were generated by HMM, with the young group showing higher fractional occupancy and mean dwell time in states 1, 3, and 4 (SY1, SY2 and SY3), and the older group in states 2, 5, and 6 (SO1, SO2 and SO3). Importantly, comparisons of transition probabilities revealed that the older group showed a reduced brain ability to transition into states dominated by the younger group, as well as a diminished capacity to persist in them. Moreover, graph analysis revealed that these young-specific states exhibited higher modularity and k-coreness. Collectively, these findings suggested that the older group showed impaired brain ability of both transition into and sustain well spatially organized states. This emphasized that the temporal changes in brain state organization, rather than its static mode, could be a key biomarker for detecting age-related functional decline. These insights may pave the way for targeted interventions aimed at mitigating cognitive decline in the aging population.

内在的大脑功能网络组织随着年龄的增长而不断变化。通过整合空间和时间信息，大脑网络如何在时间上重新配置并保持井井有条的空间结构的过程在很大程度上反映了大脑功能，因此有可能捕捉其与年龄相关的衰退。在这项研究中，我们使用隐马尔可夫模型 （HMM） 检查了健康年轻人和老年人的静息态功能磁共振成像 （fMRI） 数据的时空大脑动力学。HMM 生成了 6 种大脑状态，年轻组在状态 1、3 和 4 （SY1、SY2 和 SY3） 中表现出较高的分数占用率和平均停留时间，而年长组在状态 2、 5 和 6 （SO1、SO2 和 SO3）中表现出更高的占有率和平均停留时间。重要的是，转换概率的比较表明，老年组的大脑过渡到由年轻组主导的状态的能力降低，以及持续存在这些状态的能力降低。此外，图分析显示，这些 young 特异性状态表现出更高的模块化和 k-coreness。总的来说，这些发现表明，老年组在过渡到和维持空间组织良好的状态方面的大脑能力受损。这强调了大脑状态组织的时间变化，而不是其静态模式，可能是检测与年龄相关的功能下降的关键生物标志物。这些见解可能为旨在缓解老龄化人口认知能力下降的针对性干预措施铺平道路。