Development of brain structural connectivity between ages 12 and 30: A 4-Tesla diffusion imaging study in 439 adolescents and adults
Development of brain structural connectivity between ages 12 and 30: A 4-Tesla diffusion imaging study in 439 adolescents and adults
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DOI：
10.1016/j.neuroimage.2012.09.004
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发表时间：
2013-01-01
期刊：
影响因子：
5.7
通讯作者：
Thompson, Paul M.
中科院分区：
文献类型：
--
作者：
Dennis, Emily L.;Jahanshad, Neda;Thompson, Paul M.
了解健康个体中的大脑在评估与精神病和神经发育障碍正常发展的偏差至关重要的情况下至关重要。大脑的解剖网络在童年和成年期之间深刻重新建模，而扩散的拖拉术具有前所未有的力量来重建体内这些网络和神经途径。在这里，我们跟踪了439名12至30岁的右撇子个体的结构连通性和网络效率的变化（211名女性/126名男性成年人，平均年龄= 23.6，SD = 2.19; 31女/24名女性/24岁男性12岁，平均年龄= 12.3 ，SD = 0.18;所有参与者在4 t时都用高角度分辨率扩散成像（HARDI）进行扫描。在我们进行全脑拖拉术后，从每个参与者的共同注册的解剖扫描中提取了70个基于皮质的基于皮质的陀螺区域。发现所有对皮质区域或节点之间的纤维连接的比例被发现产生对称纤维密度矩阵，反映了结构性大脑网络。从那70 x 70矩阵中，我们计算了表征结构连接性的图形理论指标。在整个开发过程中，几个关键的全球和节点指标都发生了变化，显示了网络集成的增加，一些连接修剪了，其他连接也得到了加强。然而，纤维密度的增加和降低并未按比例分布在整个大脑中。额叶皮层的纤维密度降低数量不成比例，而颞皮层的纤维密度增加数量不成比例。对正在发展的结构连接组的这种大规模分析为人脑的成熟奠定了基础，以制定异常大脑连通性的统计标准。 （c）2012 Elsevier Inc.保留所有权利。
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 x 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. (C) 2012 Elsevier Inc. All rights reserved.