Department of Psychology, Washington University, St. Louis, MO 63130, USA.
Neuroimage. 2010 Feb 15;49(4):3132-48. doi: 10.1016/j.neuroimage.2009.11.001. Epub 2009 Nov 10.
Recent advances in brain connectivity methods have made it possible to identify hubs-the brain's most globally connected regions. Such regions are essential for coordinating brain functions due to their connectivity with numerous regions with a variety of specializations. Current structural and functional connectivity methods generally agree that default mode network (DMN) regions have among the highest global brain connectivity (GBC). We developed two novel statistical approaches using resting state functional connectivity MRI-weighted and unweighted GBC (wGBC and uGBC)-to test the hypothesis that the highest global connectivity also occurs in the cognitive control network (CCN), a network anti-correlated with the DMN across a variety of tasks. High global connectivity was found in both CCN and DMN. The newly developed wGBC approach improves upon existing methods by quantifying inter-subject consistency, quantifying the highest GBC values by percentage, and avoiding arbitrarily connection strength thresholding. The uGBC approach is based on graph theory and includes many of these improvements, but still requires an arbitrary connection threshold. We found high GBC in several subcortical regions (e.g., hippocampus, basal ganglia) only with wGBC despite the regions' extensive anatomical connectivity. These results demonstrate the complementary utility of wGBC and uGBC analyses for the characterization of the most highly connected, and thus most functionally important, regions of the brain. Additionally, the high connectivity of both the CCN and the DMN demonstrates that brain regions outside primary sensory-motor networks are highly involved in coordinating information throughout the brain.
近年来,脑连接方法的进步使得识别大脑中连接最广泛的区域(即枢纽)成为可能。由于与具有各种专业化的众多区域的连接,这些区域对于协调大脑功能至关重要。目前的结构和功能连接方法普遍认为,默认模式网络(DMN)区域具有最高的全局脑连接(GBC)。我们开发了两种使用静息状态功能连接磁共振成像加权和非加权 GBC(wGBC 和 uGBC)的新统计方法,以检验以下假设:即最高的全局连通性也发生在认知控制网络(CCN)中,该网络与 DMN 在各种任务中呈反相关。在 CCN 和 DMN 中均发现了较高的全局连通性。新开发的 wGBC 方法通过量化受试者间一致性、以百分比量化最高 GBC 值以及避免任意连接强度阈值来改进现有方法。uGBC 方法基于图论,并包含许多这些改进,但仍需要任意连接阈值。尽管这些区域具有广泛的解剖连接性,但我们仅使用 wGBC 发现了几个皮质下区域(例如海马体、基底神经节)的高 GBC。这些结果表明,wGBC 和 uGBC 分析对于表征大脑中连接最广泛且因此功能最重要的区域具有互补的作用。此外,CCN 和 DMN 的高连通性表明,除了主要感觉运动网络之外,大脑区域在协调整个大脑中的信息方面也起着重要作用。