Liu Zijin, Xia Haishuo, Chen Antao
School of Psychology, Research Center for Exercise and Brain Science, Shanghai University of Sport, Shanghai, 200082, China.
Faculty of Psychology, Southwest University, Chongqing, 400700, China.
Geroscience. 2025 Apr;47(2):1761-1776. doi: 10.1007/s11357-024-01366-y. Epub 2024 Oct 3.
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.
大脑内在功能网络组织会随着衰老而持续变化。通过整合空间和时间信息，大脑网络在时间上重新配置并保持良好组织的空间结构的过程，在很大程度上反映了大脑功能，因此有潜力捕捉与年龄相关的衰退。在本研究中，我们使用隐马尔可夫模型（HMM），从健康年轻人和老年人的静息态功能磁共振成像（fMRI）数据中检查了大脑的时空动态。HMM生成了六种大脑状态，年轻组在状态1、3和4（SY1、SY2和SY3）中显示出更高的分数占有率和平均停留时间，而老年组在状态2、5和6（SO1、SO2和SO3）中显示出更高的分数占有率和平均停留时间。重要的是，转移概率的比较显示，老年组向由年轻组主导的状态转变的大脑能力降低，并且在这些状态中持续存在的能力也减弱。此外，图分析显示，这些特定于年轻人的状态表现出更高的模块化和k-核性。总体而言，这些发现表明，老年组向空间组织良好的状态转变和维持的大脑能力受损。这强调了大脑状态组织的时间变化，而非其静态模式，可能是检测与年龄相关的功能衰退的关键生物标志物。这些见解可能为旨在减轻老年人群认知衰退的靶向干预措施铺平道路。
