Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany.
IDeA Center for Individual Development and Adaptive Education, Frankfurt am Main, Germany.
Hum Brain Mapp. 2020 Feb 1;41(2):362-372. doi: 10.1002/hbm.24807. Epub 2019 Oct 6.
Individual differences in general cognitive ability (i.e., intelligence) have been linked to individual variations in the modular organization of functional brain networks. However, these analyses have been limited to static (time-averaged) connectivity, and have not yet addressed whether dynamic changes in the configuration of brain networks relate to general intelligence. Here, we used multiband functional MRI resting-state data (N = 281) and estimated subject-specific time-varying functional connectivity networks. Modularity optimization was applied to determine individual time-variant module partitions and to assess fluctuations in modularity across time. We show that higher intelligence, indexed by an established composite measure, the Wechsler Abbreviated Scale of Intelligence (WASI), is associated with higher temporal stability (lower temporal variability) of brain network modularity. Post-hoc analyses reveal that subjects with higher intelligence scores engage in fewer periods of extremely high modularity - which are characterized by greater disconnection of task-positive from task-negative networks. Further, we show that brain regions of the dorsal attention network contribute most to the observed effect. In sum, our study suggests that investigating the temporal dynamics of functional brain network topology contributes to our understanding of the neural bases of general cognitive abilities.
个体在一般认知能力(即智力)上的差异与大脑功能网络模块化组织的个体差异有关。然而,这些分析仅限于静态(时间平均)连通性,尚未解决大脑网络结构的动态变化是否与一般智力有关。在这里,我们使用多频段功能磁共振成像静息态数据(N=281),并估计了个体随时间变化的功能连通性网络。我们采用模块化优化来确定个体时变模块分区,并评估模块性随时间的波动。我们发现,较高的智力(由一项已建立的综合指标——韦氏简明智力量表(WASI)来衡量)与大脑网络模块性的时间稳定性(较低的时间可变性)相关。事后分析表明,智力得分较高的受试者经历了较少的极高模块性时期——这些时期的特征是任务正性网络与任务负性网络的连接性更大。此外,我们还表明,背侧注意网络的脑区对观察到的效应贡献最大。总之,我们的研究表明,研究功能大脑网络拓扑的时间动态有助于我们理解一般认知能力的神经基础。