The hubs of the human connectome are generally implicated in the anatomy of brain disorders.
The hubs of the human connectome are generally implicated in the anatomy of brain disorders.
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DOI：
10.1093/brain/awu132
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发表时间：
2014-08
期刊：
影响因子：
--
通讯作者：
Bullmore ET
中科院分区：
文献类型：
--
作者：
Crossley NA;Mechelli A;Scott J;Carletti F;Fox PT;McGuire P;Bullmore ET
参见Sporns（doi：）以获得对本文的科学评论。脑网络包含少数高度连接的枢纽节点，具有高拓扑价值和生物成本。通过对健康志愿者的DTI数据进行网络分析，以及对26种脑部疾病的已发表MRI研究进行荟萃分析，Crossley等人发现，各种疾病的病变往往集中在枢纽。大脑网络或“连接组”包括少数高度连接的枢纽节点，这些节点在功能上很有价值，因为它们的拓扑中心性支持综合处理和适应行为。最近的研究还表明，枢纽比其他大脑区域有更高的代谢需求和更长的距离连接，因此可以被认为是生物学上的代价。假设枢纽通常联合收割机了高拓扑价值和高生物成本，我们预测病理性脑损伤将集中在枢纽区域。为了验证这一一般假设，我们首先确定了健康志愿者（n = 56）的弥散张量成像数据估计的大脑解剖网络的枢纽，并表明与随机攻击相比，针对枢纽的计算攻击会降低大脑网络的效率。然后，我们根据对20000多名受试者和26种不同脑部疾病的已发表磁共振成像数据的荟萃分析，准备了灰质病变图。所有脑部疾病中常见的磁共振成像病变更可能位于正常大脑连接体的枢纽（P < 10−4，排列检验）。具体来说，9种脑部疾病的病变更有可能位于中枢（P < 0.05，排列检验），包括精神分裂症和阿尔茨海默病。这两种疾病有显着的集线器集中的病变分布，虽然（几乎完全）不同的子集的皮质枢纽病变在每种疾病：颞叶枢纽特别是与阿尔茨海默病的病变概率较高，而在精神分裂症病变集中在额叶和颞叶皮质枢纽。这些结果将病理性病变与正常扩散张量成像连接体中节点的拓扑中心性联系起来，当通过对健康志愿者的1500多项任务相关功能神经成像研究进行荟萃分析以创建规范的功能共激活网络来定义枢纽时，这些结果通常可以复制。我们的结论是，在许多（如果不是全部）大脑疾病中，人脑网络的高成本/高价值枢纽在解剖学上比非枢纽更有可能是异常的。
See Sporns (doi:) for a scientific commentary on this article. Brain networks contain a minority of highly connected hub nodes with high topological value and biological cost. Using network analysis of DTI data from healthy volunteers, and meta-analyses of published MRI studies in 26 brain disorders, Crossley et al. show that lesions across disorders tend to be concentrated at hubs. Brain networks or ‘connectomes’ include a minority of highly connected hub nodes that are functionally valuable, because their topological centrality supports integrative processing and adaptive behaviours. Recent studies also suggest that hubs have higher metabolic demands and longer-distance connections than other brain regions, and therefore could be considered biologically costly. Assuming that hubs thus normally combine both high topological value and high biological cost, we predicted that pathological brain lesions would be concentrated in hub regions. To test this general hypothesis, we first identified the hubs of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n = 56), and showed that computational attacks targeted on hubs disproportionally degraded the efficiency of brain networks compared to random attacks. We then prepared grey matter lesion maps, based on meta-analyses of published magnetic resonance imaging data on more than 20 000 subjects and 26 different brain disorders. Magnetic resonance imaging lesions that were common across all brain disorders were more likely to be located in hubs of the normal brain connectome (P < 10−4, permutation test). Specifically, nine brain disorders had lesions that were significantly more likely to be located in hubs (P < 0.05, permutation test), including schizophrenia and Alzheimer’s disease. Both these disorders had significantly hub-concentrated lesion distributions, although (almost completely) distinct subsets of cortical hubs were lesioned in each disorder: temporal lobe hubs specifically were associated with higher lesion probability in Alzheimer’s disease, whereas in schizophrenia lesions were concentrated in both frontal and temporal cortical hubs. These results linking pathological lesions to the topological centrality of nodes in the normal diffusion tensor imaging connectome were generally replicated when hubs were defined instead by the meta-analysis of more than 1500 task-related functional neuroimaging studies of healthy volunteers to create a normative functional co-activation network. We conclude that the high cost/high value hubs of human brain networks are more likely to be anatomically abnormal than non-hubs in many (if not all) brain disorders.
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影响因子：
4.3
作者：
de Haan W;Mott K;van Straaten EC;Scheltens P;Stam CJ
通讯作者：
Stam CJ
影响因子：
4.8
作者：
Eickhoff, Simon B.;Laird, Angela R.;Grefkes, Christian;Wang, Ling E.;Zilles, Karl;Fox, Peter T.
通讯作者：
Fox, Peter T.
影响因子：
5.3
作者：
Achard, S;Salvador, R;Bullmore, ET
通讯作者：
Bullmore, ET
影响因子：
48
作者：
Craddock, R. Cameron;Jbabdi, Saad;Yan, Chao-Gan;Vogelstein, Joshua T.;Castellanos, F. Xavier;Di Martino, Adriana;Kelly, Clare;Heberlein, Keith;Colcombe, Stan;Milham, Michael P.
通讯作者：
Milham, Michael P.
DOI：
10.1073/pnas.1220826110
发表时间：
2013-07-09
影响因子：
11.1
作者：
Crossley, Nicolas A.;Mechelli, Andrea;Bullmore, Edward T.
通讯作者：
Bullmore, Edward T.