The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR China.
MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China.
Transl Psychiatry. 2020 May 13;10(1):147. doi: 10.1038/s41398-020-0829-3.
Neuroimaging studies have uncovered the neural roots of individual differences in human general fluid intelligence (Gf). Gf is characterized by the function of specific neural circuits in brain gray-matter; however, the association between Gf and neural function in brain white-matter (WM) remains unclear. Given reliable detection of blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals in WM, we used a functional, rather than an anatomical, neuromarker in WM to identify individual Gf. We collected longitudinal BOLD-fMRI data (in total three times, ~11 months between time 1 and time 2, and ~29 months between time 1 and time 3) in normal volunteers at rest, and identified WM functional connectomes that predicted the individual Gf at time 1 (n = 326). From internal validation analyses, we demonstrated that the constructed predictive model at time 1 predicted an individual's Gf from WM functional connectomes at time 2 (time 1 ∩ time 2: n = 105) and further at time 3 (time 1 ∩ time 3: n = 83). From external validation analyses, we demonstrated that the predictive model from time 1 was generalized to unseen individuals from another center (n = 53). From anatomical aspects, WM functional connectivity showing high predictive power predominantly included the superior longitudinal fasciculus system, deep frontal WM, and ventral frontoparietal tracts. These results thus demonstrated that WM functional connectomes offer a novel applicable neuromarker of Gf and supplement the gray-matter connectomes to explore brain-behavior relationships.
神经影像学研究揭示了人类一般流体智力(Gf)个体差异的神经基础。Gf 的特征是大脑灰质中特定神经回路的功能;然而,Gf 与大脑白质(WM)中的神经功能之间的关联尚不清楚。鉴于在 WM 中可靠地检测到血氧水平依赖功能磁共振成像(BOLD-fMRI)信号,我们使用 WM 中的功能而不是解剖学神经标志物来识别个体 Gf。我们在静息状态下收集了正常志愿者的纵向 BOLD-fMRI 数据(总共三次,第一次和第二次之间约 11 个月,第一次和第三次之间约 29 个月),并确定了可预测个体 Gf 的 WM 功能连接组(n=326)。通过内部验证分析,我们证明了在第一次时构建的预测模型可以从 WM 功能连接组预测个体的 Gf(时间 1∩时间 2:n=105),并且进一步预测到时间 3(时间 1∩时间 3:n=83)。通过外部验证分析,我们证明了来自第一次的预测模型可以推广到来自另一个中心的未见过的个体(n=53)。从解剖学方面来看,具有高预测能力的 WM 功能连接主要包括上纵束系统、深部额 WM 和腹侧额顶叶束。因此,这些结果表明 WM 功能连接组提供了一种新颖的 Gf 适用神经标志物,并补充了灰质连接组来探索大脑-行为关系。