论文标题
基于强大的电路的人体脑区域的结构重要性得分
Robust Circuitry-Based Scores of Structural Importance of Human Brain Areas
论文作者
论文摘要
我们考虑从1064名受试者的扩散MRI数据计算出的1015-Vertex人共识连接组。我们在这1015个图形顶点上定义了七个不同的订单，其中订单取决于源自大脑电路的参数，即从入射的边缘（或连接）到订购的顶点的属性（或连接）的属性。我们根据其程度，总和，最大值和纤维的平均值对事件边缘的计数以及事件边缘中纤维的最大和平均长度进行订购。我们通过Spearman相关系数及其反演数量分析了这七个订单的相似性，并发现所有这七个订单都具有很大的相似性。换句话说，如果我们将命令解释为在共识中的顶点的重要性评分，那么在所有七个顺序中，顶点的得分都将相似。也就是说，人类连接组的重要顶点通常具有许多邻居，与长长和厚的轴突纤维连接（通过纤维数测量厚度），并且它们的入射边缘也具有高度和平均长度和纤维数参数的高最大和平均值。因此，这些参数可能会产生可靠的方式来确定哪些顶点在我们的脑电路的解剖结构中比其他参数更重要。
We consider the 1015-vertex human consensus connectome computed from the diffusion MRI data of 1064 subjects. We define seven different orders on these 1015 graph vertices, where the orders depend on parameters derived from the brain circuitry, that is, from the properties of the edges (or connections) incident to the vertices ordered. We order the vertices according to their degree, the sum, the maximum, and the average of the fiber counts on the incident edges, and the sum, the maximum and the average length of the fibers in the incident edges. We analyze the similarities of these seven orders by the Spearman correlation coefficient and by their inversion numbers and have found that all of these seven orders have great similarities. In other words, if we interpret the orders as scoring of the importance of the vertices in the consensus connectome, then the scores of the vertices will be similar in all seven orderings. That is, important vertices of the human connectome typically have many neighbors, connected with long and thick axonal fibers (where thickness is measured by fiber numbers), and their incident edges have high maximum and average values of length and fiber-number parameters, too. Therefore, these parameters may yield robust ways of deciding which vertices are more important in the anatomy of our brain circuitry than the others.
