功能性脑网络的动力学：认知任务执行过程中的整合网络状态
The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance.
作者信息
Shine James M, Bissett Patrick G, Bell Peter T, Koyejo Oluwasanmi, Balsters Joshua H, Gorgolewski Krzysztof J, Moodie Craig A, Poldrack Russell A
机构信息
Department of Psychology, Stanford University, Stanford, CA 94305, USA; Neuroscience Research Australia, University of New South Wales, Sydney NSW 2052, Australia.
Department of Psychology, Stanford University, Stanford, CA 94305, USA.
出版信息
Neuron. 2016 Oct 19;92(2):544-554. doi: 10.1016/j.neuron.2016.09.018. Epub 2016 Sep 29.
Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.
高级脑功能依赖于跨大脑区域的专门群落灵活整合信息的能力；然而，目前尚不清楚这种机制如何随时间显现。在本研究中，我们使用功能磁共振成像（fMRI）数据的时间分辨网络分析来证明，人类大脑在功能状态之间转换，这些功能状态要么使大脑最大限度地分隔成紧密联系的群落，要么使原本不同的神经区域实现整合。整合状态能在认知任务中实现更快、更准确的表现，并且与瞳孔直径的扩大有关，这表明上行神经调节系统可能控制着这些大脑功能的替代模式之间的转换。总之，我们的结果证实了认知表现与大脑网络结构的动态重组之间的直接联系。
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