Argiris Georgette, Stern Yaakov, Habeck Christian
Cognitive Neuroscience Division, Department of Neurology, Columbia University Irving Medical Center, New York, NY.
Taub Institute, Columbia University, New York, NY.
Res Sq. 2024 Dec 4:rs.3.rs-5356022. doi: 10.21203/rs.3.rs-5356022/v1.
Recent advancements in connectome analyses have enabled more precise measurements of brain network integrity. Identifying neural measures that can operate as mechanisms of cognitive reserve (CR) is integral for the study of individual variability in age-related cognitive changes. In the present study, we tested the hypothesis that network resilience, or the network's ability to maintain functionality when facing internal or external perturbations that cause damage or error, can function as a CR candidate, modifying the relationship between cognitive and brain changes in a lifespan cohort of cognitively healthy adults. One hundred cognitively healthy older adults from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (50-80 years) underwent resting-state fMRI and neuropsychological testing at baseline and five-year follow-up. Using undirected weighted adjacency matrices created from the Schaefer et al. (2018) 400-parcellation atlas and 19 additional subcortical regions (419 nodes in total), whole-brain network resilience was assessed through a targeted attack approach, where nodes were sequentially removed by nodal strength and resilience defined as the iteration of the steepest slope in the largest connected component (LCC) decay. We observed that brain resilience (BR) moderated the effect of cortical thickness (CT) changes on longitudinal changes in Fluid Reasoning performance, even after adjusting for baseline differences, demographic factors, and the initial LCC of the unlesioned matrix, indicating that individuals with greater resilience were less sensitive to the effect of cortical thickness changes on changes in cognition. These findings support the use of targeted attack as a measure of cognitive reserve, suggesting that higher brain network resilience may allow individuals with reduced brain integrity to better cope with structural loss and maintain cognitive function.
连接组分析的最新进展使得对脑网络完整性的测量更加精确。确定能够作为认知储备（CR）机制的神经测量指标，对于研究与年龄相关的认知变化中的个体差异至关重要。在本研究中，我们检验了以下假设：网络弹性，即网络在面对导致损伤或错误的内部或外部扰动时维持功能的能力，可以作为一种CR候选指标，改变认知健康成年人寿命队列中认知与脑变化之间的关系。来自参考能力神经网络（RANN）纵向寿命队列（50 - 80岁）的100名认知健康的老年人在基线和五年随访时接受了静息态功能磁共振成像（fMRI）和神经心理学测试。使用从Schaefer等人（2018年）的400分区图谱和另外19个皮质下区域（总共419个节点）创建的无向加权邻接矩阵，通过有针对性的攻击方法评估全脑网络弹性，其中节点按节点强度顺序移除，弹性定义为最大连通分量（LCC）衰减中最陡斜率的迭代次数。我们观察到，即使在调整了基线差异、人口统计学因素和未受损矩阵的初始LCC之后，脑弹性（BR）仍调节了皮质厚度（CT）变化对流体推理性能纵向变化的影响，这表明弹性较大的个体对皮质厚度变化对认知变化的影响不太敏感。这些发现支持将有针对性的攻击用作认知储备的一种测量方法，表明更高的脑网络弹性可能使脑完整性降低的个体更好地应对结构损失并维持认知功能。
