{"title":"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","authors":"","doi":"10.1016/j.plrev.2024.09.003","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":403,"journal":{"name":"Physics of Life Reviews","volume":null,"pages":null},"PeriodicalIF":13.7000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why graph theory deserves more focus. Comment on “Connectivity analyses for task-based fMRI” by Huang et al.\",\"authors\":\"\",\"doi\":\"10.1016/j.plrev.2024.09.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":403,\"journal\":{\"name\":\"Physics of Life Reviews\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":13.7000,\"publicationDate\":\"2024-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics of Life Reviews\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1571064524001143\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics of Life Reviews","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1571064524001143","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
Why graph theory deserves more focus. Comment on “Connectivity analyses for task-based fMRI” by Huang et al.
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.
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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