Default network and intelligence difference

Ming Song, Yong Liu, Yuan Zhou, Kun Wang, Chunshui Yu, Tianzi Jiang
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引用次数: 4

Abstract

In the last few years, many studies in the cognitive and system neuroscience found that a consistent network of brain regions, referred to as the default network, showed high levels of activity when no explicit task was performed. Some scientists believed that the resting state activity might reflect some neural functions that consolidate the past, stabilize brain ensembles and prepare us for the future. Here, we modeled default network as undirected weighted graph and then used graph theory to investigate the topological properties of the default network of the two groups of people with different intelligence levels. We found that, in both groups, the posterior cingulate cortex showed the greatest degree in comparison to the other brain regions in the default network, and that the medial temporal lobes and cerebellar tonsils were topologically separations from the other brain regions in the default network. More importantly, we found that the strength of some functional connectivities and the global efficiency of default network were significantly different between the superior intelligence group and the average intelligence group, which indicates that the functional integration of the default network might be related to the individual intelligent performance.
默认网络和智能的区别
在过去的几年里,认知和系统神经科学的许多研究发现,当没有执行明确的任务时,一个被称为默认网络的一致的大脑区域网络显示出高水平的活动。一些科学家认为,静息状态的活动可能反映了一些神经功能,这些功能可以巩固过去,稳定大脑整体,并为我们的未来做好准备。在此,我们将默认网络建模为无向加权图,然后利用图论研究了两组不同智力水平的人默认网络的拓扑特性。我们发现,在两组中,后扣带皮层与默认网络中的其他大脑区域相比表现出最大的程度,并且内侧颞叶和小脑扁桃体在拓扑上与默认网络中的其他大脑区域分离。更重要的是,我们发现某些功能连接的强度和默认网络的整体效率在高智力组和普通智力组之间存在显著差异,这表明默认网络的功能整合可能与个体的智能表现有关。
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