{"title":"大脑的行为像(复杂)网络吗?I. 动态","authors":"D. Papo , J.M. Buldú","doi":"10.1016/j.plrev.2023.12.006","DOIUrl":null,"url":null,"abstract":"<div><p>Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of <em>networkness</em>, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.</p></div>","PeriodicalId":403,"journal":{"name":"Physics of Life Reviews","volume":null,"pages":null},"PeriodicalIF":13.7000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1571064523002105/pdfft?md5=c53bf1891b65a3e5ac5ced1ab735afd8&pid=1-s2.0-S1571064523002105-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Does the brain behave like a (complex) network? I. Dynamics\",\"authors\":\"D. Papo , J.M. Buldú\",\"doi\":\"10.1016/j.plrev.2023.12.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of <em>networkness</em>, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.</p></div>\",\"PeriodicalId\":403,\"journal\":{\"name\":\"Physics of Life Reviews\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":13.7000,\"publicationDate\":\"2023-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1571064523002105/pdfft?md5=c53bf1891b65a3e5ac5ced1ab735afd8&pid=1-s2.0-S1571064523002105-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics of Life Reviews\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1571064523002105\",\"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/S1571064523002105","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
Does the brain behave like a (complex) network? I. Dynamics
Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of networkness, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.
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.