Yeung Hon Wah, Buchanan Colin R, Moodie Joanna, Deary Ian J, Tucker-Drob Elliot M, Bastin Mark E, Whalley Heather C, Smith Keith M, Cox Simon R
Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom.
Department of Psychology, University of Texas, Austin, TX, USA.
bioRxiv. 2025 Mar 16:2025.03.15.643458. doi: 10.1101/2025.03.15.643458.
In this work, we propose a new class of graph measures for weighted connectivity information in the human brain based on node relative strengths: relative strength variability (RSV), measuring susceptibility to targeted attacks, and hierarchical RSV (hRSV), a first weighted statistical complexity measure for networks. Using six different network weights for structural connectomes from the UK Biobank, we conduct comprehensive analyses to explore relationships between the RSV and hRSV, and (i) other known network measures, (ii) general cognitive function (' '). Both measures exhibit low correlations with other graph measures across all connectivity weightings indicating that they capture new information of the brain connectome. We found higher was associated with lower RSV and lower hRSV. That is, higher was associated with higher resistance to targeted attack and lower statistical complexity. Moreover, the proposed measures had consistently stronger associations with than other widely used graph measures including clustering coefficient and global efficiency and were incrementally significant for predicting above other measures for five of the six network weights. Overall, we present a new class of weighted network measures based on variations of relative node strengths which significantly improved prediction of general cognition from traditional weighted structural connectomes.
在这项工作中，我们基于节点相对强度提出了一类用于人类大脑加权连通性信息的新图测度：相对强度变异性（RSV），用于衡量对定向攻击的敏感性；以及层次RSV（hRSV），这是一种用于网络的首个加权统计复杂性测度。我们使用来自英国生物银行的六种不同网络权重的结构连接组，进行了全面分析，以探索RSV和hRSV与（i）其他已知网络测度、（ii）一般认知功能之间的关系。在所有连通性权重下，这两种测度与其他图测度的相关性都很低，这表明它们捕捉到了大脑连接组的新信息。我们发现较高的[具体内容缺失]与较低的RSV和较低的hRSV相关。也就是说，较高的[具体内容缺失]与对定向攻击的较高抵抗力和较低的统计复杂性相关。此外，与包括聚类系数和全局效率在内的其他广泛使用的图测度相比，所提出的测度与[具体内容缺失]的关联始终更强，并且在六个网络权重中的五个权重下，对于预测[具体内容缺失]而言，相对于其他测度具有增量显著性。总体而言，我们提出了一类基于相对节点强度变化的新的加权网络测度，它显著改善了从传统加权结构连接组对一般认知的预测。
