Using graph theory as a common language to combine neural structure and function in models of healthy cognitive performance.
Using graph theory as a common language to combine neural structure and function in models of healthy cognitive performance.
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DOI：
10.1002/hbm.26258
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发表时间：
2023-06-01
影响因子：
4.8
通讯作者：
中科院分区：
文献类型：
--
作者：
图论已被用于认知神经科学，以了解结构和功能脑网络的组织特性如何与认知功能相关。图论可以通过引入网络特征的通用度量来弥合结构和功能连通性的整合差距。然而，结构图与功能图联合理论在健康成人认知表现建模中的解释和预测价值尚未得到研究。在这项工作中，采用嵌入逐步回归的主成分回归方法来拟合执行功能、自我调节、语言、编码和序列处理的多元回归模型，并使用20种不同的图论结构和功能网络组织度量作为回归量。将基于图论的模型与基于连通性的模型的预测能力进行了比较。目前的工作表明，与直接基于结构和功能连接值进行预测相比，使用图论指标组合来预测健康人群的认知能力并没有产生一致的好处。采用逐步回归管道的主成分回归示意图。
Graph theory has been used in cognitive neuroscience to understand how organisational properties of structural and functional brain networks relate to cognitive function. Graph theory may bridge the gap in integration of structural and functional connectivity by introducing common measures of network characteristics. However, the explanatory and predictive value of combined structural and functional graph theory have not been investigated in modelling of cognitive performance of healthy adults. In this work, a Principal Component Regression approach with embedded Step‐Wise Regression was used to fit multiple regression models of Executive Function, Self‐regulation, Language, Encoding and Sequence Processing with a collection of 20 different graph theoretic measures of structural and functional network organisation used as regressors. The predictive ability of graph theory‐based models was compared to that of connectivity‐based models. The present work shows that using combinations of graph theory metrics to predict cognition in healthy populations does not produce a consistent benefit relative to making predictions based on structural and functional connectivity values directly. Schematic presenting the principal component regression with step‐wise regression pipeline.
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影响因子：
5.7
作者：
Dale, AM;Fischl, B;Sereno, MI
通讯作者：
Sereno, MI
DOI：
10.1073/pnas.1315529111
发表时间：
2014-01-14
影响因子：
11.1
作者：
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通讯作者：
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DOI：
10.1073/pnas.1501242112
发表时间：
2015-07-14
影响因子：
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作者：
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通讯作者：
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影响因子：
2.9
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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