The length and the width of the human brain circuit connections are strongly correlated.

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES
Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-09 DOI:10.1007/s11571-024-10201-1
Dániel Hegedűs, Vince Grolmusz
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引用次数: 0

Abstract

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.

人类大脑回路连接的长度和宽度是紧密相关的。
共识连接组由 1064 个 braingraphs 构建而成,每个 braingraphs 有 1015 个顶点,对应 1015 个大脑解剖区域。所研究的属性包括边缘长度、纤维数或边缘宽度(即形成边缘的轴突束的发现数量)以及边缘的出现次数(即存在边缘的单个布拉因图的数量)。通过使用我们之前在 https://braingraph.org 上发布的稳健 braingraphs,我们从数据中准备了一个单一的共识图,并比较了边缘出现数、边缘长度和边缘纤维数的统计相似性。我们发现边缘出现数和纤维数之间存在很强的 Spearman 正相关性,这表明从统计学角度看,最频繁的大脑连接具有最大的宽度,即纤维数。我们发现,纤维长度与纤维数之间存在负的斯皮尔曼相关性,这表明,通常情况下,最短的边缘在纤维数上是最宽或最强的。我们还发现,出现次数与边缘长度之间存在负的斯皮尔曼相关性:这表明,通常情况下,长边缘不常见,而常见的边缘较短。
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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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