Hegedűs Dániel, Grolmusz Vince
PIT Bioinformatics Group, Eötvös University, Budapest, H-1117 Hungary.
Uratim Ltd., Budapest, H-1118 Hungary.
Cogn Neurodyn. 2025 Dec;19(1):21. doi: 10.1007/s11571-024-10201-1. Epub 2025 Jan 9.
The correlations of several fundamental properties of human brain connections are investigated in a consensus connectome, constructed from 1064 braingraphs, each on 1015 vertices, corresponding to 1015 anatomical brain areas. The properties examined include the edge length, the fiber count, or edge width, meaning the number of discovered axon bundles forming the edge and the occurrence number of the edge, meaning the number of individual braingraphs where the edge exists. By using our previously published robust braingraphs at https://braingraph.org, we have prepared a single consensus graph from the data and compared the statistical similarity of the edge occurrence numbers, edge lengths, and fiber counts of the edges. We have found a strong positive Spearman correlation between the edge occurrence numbers and the fiber count numbers, showing that statistically, the most frequent cerebral connections have the largest widths, i.e., the fiber count. We have found a negative Spearman correlation between the fiber lengths and fiber counts, showing that, typically, the shortest edges are the widest or strongest by their fiber counts. We have also found a negative Spearman correlation between the occurrence numbers and the edge lengths: it shows that typically, the long edges are infrequent, and the frequent edges are short.
在一个由1064个脑图谱构建的共识连接组中,研究了人类大脑连接的几个基本属性之间的相关性。这些脑图谱中的每一个都有1015个顶点,对应于1015个解剖学脑区。所研究的属性包括边长度、纤维数量(或边宽度,即构成边的已发现轴突束的数量)以及边的出现次数(即边存在的个体脑图谱的数量)。通过使用我们之前在https://braingraph.org上发布的可靠脑图谱,我们从数据中制备了一个单一的共识图,并比较了边的出现次数、边长度和纤维数量的统计相似性。我们发现边的出现次数与纤维数量之间存在很强的正斯皮尔曼相关性,这表明从统计学角度来看,最频繁的脑连接具有最大的宽度,即纤维数量。我们发现纤维长度与纤维数量之间存在负斯皮尔曼相关性,这表明通常情况下,最短的边按其纤维数量来说是最宽或最强的。我们还发现出现次数与边长度之间存在负斯皮尔曼相关性:这表明通常情况下,长边出现的频率低,而频繁出现的边较短。