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本文引用的文献

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LEFT VERSUS RIGHT HEMISPHERE DIFFERENCES IN BRAIN CONNECTIVITY: 4-TESLA HARDI TRACTOGRAPHY IN 569 TWINS.大脑连接性的左右半球差异:569对双胞胎的4特斯拉高分辨率扩散张量成像研究
Proc IEEE Int Symp Biomed Imaging. 2012 May;2012:526-529. doi: 10.1109/ISBI.2012.6235601.
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Test-retest reliability of graph theory measures of structural brain connectivity.脑结构连接性的图论测量方法的重测信度。
Med Image Comput Comput Assist Interv. 2012;15(Pt 3):305-12. doi: 10.1007/978-3-642-33454-2_38.
3
DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME.影响人类大脑连接性的基因发现:连接组的全基因组分析
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CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS.12至30岁间大脑解剖学连接性的变化:一项针对467名青少年及成年人的高分辨率扩散成像研究
Proc IEEE Int Symp Biomed Imaging. 2012:904-908. doi: 10.1109/ISBI.2012.6235695.
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HOW DO SPATIAL AND ANGULAR RESOLUTION AFFECT BRAIN CONNECTIVITY MAPS FROM DIFFUSION MRI?空间分辨率和角度分辨率如何影响扩散磁共振成像的脑连接图谱?
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Developmental changes in organization of structural brain networks.结构脑网络组织的发育变化。
Cereb Cortex. 2013 Sep;23(9):2072-85. doi: 10.1093/cercor/bhs187. Epub 2012 Jul 10.
7
Angular versus spatial resolution trade-offs for diffusion imaging under time constraints.在时间受限的情况下,扩散成像的角分辨率与空间分辨率的权衡。
Hum Brain Mapp. 2013 Oct;34(10):2688-706. doi: 10.1002/hbm.22094. Epub 2012 Apr 21.
8
Altered structural brain connectivity in healthy carriers of the autism risk gene, CNTNAP2.自闭症风险基因 CNTNAP2 健康携带者的大脑结构连接改变。
Brain Connect. 2011;1(6):447-59. doi: 10.1089/brain.2011.0064.
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Brain network local interconnectivity loss in aging APOE-4 allele carriers.衰老 APOE-4 等位基因携带者的脑网络局部连通性丧失。
Proc Natl Acad Sci U S A. 2011 Dec 20;108(51):20760-5. doi: 10.1073/pnas.1109038108. Epub 2011 Nov 21.
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Functional brain network efficiency predicts intelligence.功能性脑网络效率可预测智力。
Hum Brain Mapp. 2012 Jun;33(6):1393-406. doi: 10.1002/hbm.21297. Epub 2011 May 9.

12 至 30 岁大脑结构连接的发展:439 名青少年和成年人的 4 特斯拉弥散成像研究。

Development of brain structural connectivity between ages 12 and 30: a 4-Tesla diffusion imaging study in 439 adolescents and adults.

机构信息

Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA 90095-7334, USA.

出版信息

Neuroimage. 2013 Jan 1;64:671-84. doi: 10.1016/j.neuroimage.2012.09.004. Epub 2012 Sep 14.

DOI:10.1016/j.neuroimage.2012.09.004
PMID:22982357
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3603574/
Abstract

Understanding how the brain matures in healthy individuals is critical for evaluating deviations from normal development in psychiatric and neurodevelopmental disorders. The brain's anatomical networks are profoundly re-modeled between childhood and adulthood, and diffusion tractography offers unprecedented power to reconstruct these networks and neural pathways in vivo. Here we tracked changes in structural connectivity and network efficiency in 439 right-handed individuals aged 12 to 30 (211 female/126 male adults, mean age=23.6, SD=2.19; 31 female/24 male 12 year olds, mean age=12.3, SD=0.18; and 25 female/22 male 16 year olds, mean age=16.2, SD=0.37). All participants were scanned with high angular resolution diffusion imaging (HARDI) at 4 T. After we performed whole brain tractography, 70 cortical gyral-based regions of interest were extracted from each participant's co-registered anatomical scans. The proportion of fiber connections between all pairs of cortical regions, or nodes, was found to create symmetric fiber density matrices, reflecting the structural brain network. From those 70 × 70 matrices we computed graph theory metrics characterizing structural connectivity. Several key global and nodal metrics changed across development, showing increased network integration, with some connections pruned and others strengthened. The increases and decreases in fiber density, however, were not distributed proportionally across the brain. The frontal cortex had a disproportionate number of decreases in fiber density while the temporal cortex had a disproportionate number of increases in fiber density. This large-scale analysis of the developing structural connectome offers a foundation to develop statistical criteria for aberrant brain connectivity as the human brain matures.

摘要

了解健康个体的大脑如何发育对于评估精神和神经发育障碍中正常发育的偏差至关重要。大脑的解剖网络在儿童期到成年期之间经历了深刻的重塑,扩散轨迹提供了前所未有的力量来重建这些网络和神经通路。在这里,我们跟踪了 439 名右利手个体(211 名女性/126 名男性成年人,平均年龄=23.6,标准差=2.19;31 名女性/24 名男性 12 岁儿童,平均年龄=12.3,标准差=0.18;25 名女性/22 名男性 16 岁儿童,平均年龄=16.2,标准差=0.37)的结构连接和网络效率的变化。所有参与者均在 4T 下进行高角度分辨率扩散成像(HARDI)扫描。在我们进行全脑轨迹追踪后,从每个参与者的配准解剖扫描中提取了 70 个皮质回状基于区域的感兴趣区。所有皮质区域之间纤维连接的比例,或者节点,被发现创建了对称的纤维密度矩阵,反映了结构大脑网络。从这些 70×70 矩阵中,我们计算了描述结构连接的图论度量。几个关键的全局和节点度量在整个发育过程中发生了变化,表现出网络整合的增加,一些连接被修剪,而另一些连接得到加强。然而,纤维密度的增加和减少并非在整个大脑中按比例分布。额叶皮质的纤维密度减少数量不成比例,而颞叶皮质的纤维密度增加数量不成比例。对发育中的结构连接组的这项大规模分析为人类大脑成熟时异常脑连接提供了统计标准的发展基础。