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脑解剖网络与智力

Brain anatomical network and intelligence.

作者信息

Li Yonghui, Liu Yong, Li Jun, Qin Wen, Li Kuncheng, Yu Chunshui, Jiang Tianzi

机构信息

LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

出版信息

PLoS Comput Biol. 2009 May;5(5):e1000395. doi: 10.1371/journal.pcbi.1000395. Epub 2009 May 29.

Abstract

Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.

摘要

直观地说,可能会认为更高的智力对应于大脑中更高效的信息传递,但从脑网络的角度来看,尚未有直接证据报道。在本研究中,我们进行了广泛的分析,以检验智力的个体差异与脑结构组织相关这一假设,特别是智力测试得分越高与脑解剖网络的更高全局效率相关。我们利用扩散张量纤维束成像技术在79名健康年轻成年人中构建了二元和加权脑解剖网络,并使用图论方法计算了网络的拓扑特性。根据智商测试得分,所有受试者被分为一般智力组和高智力组,发现后一组的网络全局效率显著更高。此外,在控制年龄和性别的情况下,我们发现所有受试者的智商得分与网络特性之间存在显著相关性。具体而言,更高的智力得分对应于网络更短的特征路径长度和更高的全局效率,表明大脑中存在更高效的并行信息传递。不仅在二元网络中,而且在加权网络中都一致观察到了这些结果,这共同为我们的假设提供了趋同证据。我们的研究结果表明,脑结构组织的效率可能是智力的重要生物学基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42bf/2683575/2675d7b9ddf3/pcbi.1000395.g001.jpg

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