Department of Electrical and Computer Engineering, ASTAR-NUS Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Networks Program, National University of Singapore, Singapore, Singapore.
Center for Brain and Cognition, Department of Technology and Information, Universitat Pompeu Fabra, Barcelona, Spain.
Sci Adv. 2019 Jan 9;5(1):eaat7854. doi: 10.1126/sciadv.aat7854. eCollection 2019 Jan.
We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the estimated model parameters revealed a large-scale cortical gradient. At one end, sensorimotor regions had strong recurrent connections and excitatory subcortical inputs, consistent with localized processing of external stimuli. At the opposing end, default network regions had weak recurrent connections and excitatory subcortical inputs, consistent with their role in internal thought. Furthermore, recurrent connection strength and subcortical inputs provided complementary information for differentiating the levels of the hierarchy, with only the former showing strong associations with other macroscale and microscale proxies of cortical hierarchies (meta-analysis of cognitive functions, principal resting fMRI gradient, myelin, and laminar-specific neuronal density). Overall, this study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain.
我们考虑了一个具有区域特定微观特性的大规模人类大脑皮层动力学电路模型。该模型使用随机优化方法进行了反演，对新的、样本外静息功能磁共振成像（fMRI）数据的拟合效果明显更好。该模型没有假设存在层次结构，估计的模型参数显示出大规模的皮质梯度。在一端，感觉运动区域具有强大的递归连接和兴奋性皮质下输入，与外部刺激的局部处理一致。在另一端，默认网络区域具有较弱的递归连接和兴奋性皮质下输入，与它们在内部思考中的作用一致。此外，递归连接强度和皮质下输入为区分层次结构的水平提供了互补信息，只有前者与皮质层次结构的其他宏观和微观代理（认知功能的荟萃分析、主要静息 fMRI 梯度、髓鞘和层特异性神经元密度）表现出强烈的关联。总的来说，这项研究从微观角度揭示了动态静息大脑中的宏观皮质层次结构。
