Kerepesi Csaba, Varga Bálint, Szalkai Balázs, Grolmusz Vince
PIT Bioinformatics Group, Eötvös University, H-1117 Budapest, Hungary; Institute for Computer Science and Control (MTA SZTAKI), Hungarian Academy of Sciences.
PIT Bioinformatics Group, Eötvös University, H-1117 Budapest, Hungary.
Neurosci Lett. 2018 Apr 23;673:51-55. doi: 10.1016/j.neulet.2018.02.052. Epub 2018 Feb 26.
In the applications of the graph theory, it is unusual that one considers numerous, pairwise different graphs on the very same set of vertices. In the case of human braingraphs or connectomes, however, this is the standard situation: the nodes correspond to anatomically identified cerebral regions, and two vertices are connected by an edge if a diffusion MRI-based workflow identifies a fiber of axons, running between the two regions, corresponding to the two vertices. Therefore, if we examine the braingraphs of n subjects, then we have n graphs on the very same, anatomically identified vertex set. It is a natural idea to describe the k-frequently appearing edges in these graphs: the edges that are present between the same two vertices in at least k out of the n graphs. Based on the NIH-funded large Human Connectome Project's public data release, we have reported the construction of the Budapest Reference Connectome Server http://www.connectome.pitgroup.org that generates and visualizes these k-frequently appearing edges. We call the graphs of the k-frequently appearing edges "k-consensus connectomes" since an edge could be included only if it is present in at least k graphs out of n. Considering the whole human brain, we have reported a surprising property of these consensus connectomes earlier. In the present work we are focusing on the frontal lobe of the brain, and we report here a similarly surprising dynamical property of the consensus connectomes when k is gradually changed from k = n to k = 1: the connections between the nodes of the frontal lobe are seemingly emanating from those nodes that were connected to sub-cortical structures of the dorsal striatum: the caudate nucleus, and the putamen. We hypothesize that this dynamic behavior copies the axonal fiber development of the frontal lobe. An animation of the phenomenon is presented at https://youtu.be/wBciB2eW6_8.
在图论的应用中,在同一组顶点上考虑众多两两不同的图是不常见的。然而,在人类脑图或连接组的情况下,这却是标准情形:节点对应于通过解剖学确定的脑区,如果基于扩散磁共振成像的工作流程识别出在两个对应于这两个顶点的区域之间运行的轴突纤维,那么这两个顶点就由一条边相连。因此,如果我们检查n个受试者的脑图,那么我们就有n个图,它们基于同一个通过解剖学确定的顶点集。描述这些图中出现k次及以上的边是一个很自然的想法:即在n个图中至少k个图里出现在相同两个顶点之间的边。基于美国国立卫生研究院资助的大型人类连接组计划的公开数据发布,我们报告了布达佩斯参考连接组服务器http://www.connectome.pitgroup.org的构建,该服务器可生成并可视化这些出现k次及以上的边。我们将出现k次及以上的边所构成的图称为“k - 共识连接组”,因为一条边只有在n个图中至少k个图里出现时才会被包含在内。考虑到整个人脑,我们之前已经报告过这些共识连接组的一个惊人特性。在当前工作中,我们聚焦于大脑的额叶,并且在此报告当k从k = n逐渐变化到k = 1时,共识连接组的一个类似惊人的动态特性:额叶节点之间的连接似乎源自那些与背侧纹状体的皮质下结构相连的节点,即尾状核和壳核。我们假设这种动态行为复制了额叶的轴突纤维发育过程。该现象的动画展示可在https://youtu.be/wBciB2eW6_8查看。