Why graph theory deserves more focus. Comment on “Connectivity analyses for task-based fMRI” by Huang et al.

IF 13.7 1区 生物学 Q1 BIOLOGY Physics of Life Reviews Pub Date : 2024-09-05 DOI:10.1016/j.plrev.2024.09.003
Mohammadreza Khodaei , Clayton C. McIntyre , Haley A. Kirse , Paul Laurienti
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Abstract

Huang et al. have conducted a thorough examination of methodologies used for identifying and analyzing functional connectivity using task-based fMRI. Their review adeptly describes current approaches without bias or preference. In this commentary, we explain why we believe that graph theory is the optimal approach for studying neural mechanisms associated with complex behaviors and cognitive processes that are engaged during task-based fMRI.

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图论为何值得更多关注?就 Huang 等人的 "基于任务的 fMRI 的连接性分析 "发表评论
Huang 等人对使用基于任务的 fMRI 识别和分析功能连接的方法进行了深入研究。他们的综述巧妙地描述了当前的方法,没有偏见或偏好。在这篇评论中,我们将解释为什么我们认为图论是研究与复杂行为和认知过程相关的神经机制的最佳方法,这些复杂行为和认知过程是在基于任务的 fMRI 过程中参与的。
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来源期刊
Physics of Life Reviews
Physics of Life Reviews 生物-生物物理
CiteScore
20.30
自引率
14.50%
发文量
52
审稿时长
8 days
期刊介绍: Physics of Life Reviews, published quarterly, is an international journal dedicated to review articles on the physics of living systems, complex phenomena in biological systems, and related fields including artificial life, robotics, mathematical bio-semiotics, and artificial intelligent systems. Serving as a unifying force across disciplines, the journal explores living systems comprehensively—from molecules to populations, genetics to mind, and artificial systems modeling these phenomena. Inviting reviews from actively engaged researchers, the journal seeks broad, critical, and accessible contributions that address recent progress and sometimes controversial accounts in the field.
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