Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, VIC 3010, Australia;Melbourne School of Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia;
Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, VIC 3010, Australia;Monash Clinical and Imaging Neuroscience, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC 3168, Australia;
Proc Natl Acad Sci U S A. 2014 Jul 15;111(28):10341-6. doi: 10.1073/pnas.1400181111. Epub 2014 Jun 30.
Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and fronto-parietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure.
神经元动力学呈现出复杂的时空结构，涉及到大量空间分布区域中激活模式的精确、上下文相关的协调。功能磁共振成像（fMRI）在证明这些相互作用的非平凡空间和拓扑结构方面发挥了核心作用，但迄今为止，它在研究其时间演变方面的能力有限。在这里，我们使用从人类连接组计划中获得的高分辨率静息态 fMRI 数据，以亚秒的分辨率绘制了整个大脑的时分辨联，目的是了解区域之间的非平稳波动如何与人类大脑的大规模拓扑性质相关。我们报告了一系列一致的功能连接的证据，这些连接在时间上表现出明显的强度波动。最动态的连接是模块间的，连接拓扑可分离子系统的元素，并定位到默认模式和额顶叶系统的已知枢纽。我们发现，空间分布的区域会自发地在短暂的时间间隔内增加它们传递信息的效率，从而产生暂时的、全局有效的网络状态。我们的研究结果表明，大脑动力学随时间产生复杂网络性质的变化，可能在高效信息处理和代谢消耗之间取得平衡。
