Huang 黄伟杰 Weijie, Chen 陈豪杰 Haojie, Liu 刘桢钊 Zhenzhao, Dong 董心怡 Xinyi, Feng 冯国政 Guozheng, Liu 刘广芳 Guangfang, Yang 杨奡偲 Aocai, Zhang 张占军 Zhanjun, Shmuel Amir, Su 苏里 Li, Ma 马国林 Guolin, Shu 舒妮 Ni
School of Systems Science, Beijing Normal University, Beijing 100875, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
J Neurosci. 2025 Jan 29;45(5):e2139232024. doi: 10.1523/JNEUROSCI.2139-23.2024.
The human brain exhibits a high degree of individual variability in both its structure and function, which underlies intersubject differences in cognition and behavior. It was previously shown that functional connectivity is more variable in the heteromodal association cortex but less variable in the unimodal cortices. Structural connectivity (SC) is the anatomical substrate of functional connectivity, but the spatial and temporal patterns of individual variability in SC (IVSC) remain largely unknown. In the present study, we discovered a detailed and robust chart of IVSC obtained by applying diffusion MRI and tractography techniques to 1,724 adults (770 males and 954 females) from multiple imaging datasets. Our results showed that the SC exhibited the highest and lowest variability in the limbic regions and the unimodal sensorimotor regions, respectively. With increased age, higher IVSC was observed across most brain regions. Moreover, the specific spatial distribution of IVSC is related to the cortical laminar differentiation and myelination content. Finally, we proposed a modified ridge regression model to predict individual cognition and generated idiographic brain mapping, which was significantly correlated with the spatial pattern of IVSC. Overall, our findings further contribute to the understanding of the mechanisms of individual variability in brain SC and link to the prediction of individual cognitive function in adult subjects.
人类大脑在结构和功能上都表现出高度的个体变异性，这是个体间认知和行为差异的基础。先前的研究表明，异模态联合皮层的功能连接性变异性更大，而单模态皮层的功能连接性变异性较小。结构连接性（SC）是功能连接性的解剖学基础，但SC中个体变异性（IVSC）的时空模式在很大程度上仍不清楚。在本研究中，我们通过将扩散磁共振成像和纤维束成像技术应用于来自多个成像数据集的1724名成年人（770名男性和954名女性），发现了一份详细且可靠的IVSC图谱。我们的结果表明，SC在边缘区域变异性最高，而在单模态感觉运动区域变异性最低。随着年龄的增长，在大多数脑区观察到更高的IVSC。此外，IVSC的特定空间分布与皮质层分化和髓鞘含量有关。最后，我们提出了一种改进的岭回归模型来预测个体认知并生成个性化脑图谱，该图谱与IVSC的空间模式显著相关。总体而言，我们的研究结果进一步有助于理解脑SC个体变异性的机制，并与成年受试者个体认知功能的预测相关联。
