大脑组织的梯度:从方法开发到用户社区的顺利进行

Jessica Royer, Casey Paquola, Sofie L. Valk, Matthias Kirschner, Seok-Jun Hong, Bo-yong Park, Richard A. I. Bethlehem, Robert Leech, B. T. Thomas Yeo, Elizabeth Jefferies, Jonathan Smallwood, Daniel Margulies, Boris C. Bernhardt
{"title":"大脑组织的梯度:从方法开发到用户社区的顺利进行","authors":"Jessica Royer, Casey Paquola, Sofie L. Valk, Matthias Kirschner, Seok-Jun Hong, Bo-yong Park, Richard A. I. Bethlehem, Robert Leech, B. T. Thomas Yeo, Elizabeth Jefferies, Jonathan Smallwood, Daniel Margulies, Boris C. Bernhardt","doi":"arxiv-2402.11055","DOIUrl":null,"url":null,"abstract":"Multimodal neuroimaging grants a powerful in vivo window into the structure\nand function of the human brain. Recent methodological and conceptual advances\nhave enabled investigations of the interplay between large-scale spatial\ntrends, or gradients, in brain structure and function, offering a framework to\nunify principles of brain organization across multiple scales. Strong community\nenthusiasm for these techniques has been instrumental in their widespread\nadoption and implementation to answer key questions in neuroscience. Following\na brief review of current literature on this framework, this perspective paper\nwill highlight how pragmatic steps aiming to make gradient methods more\naccessible to the community propelled these techniques to the forefront of\nneuroscientific inquiry. More specifically, we will emphasize how interest for\ngradient methods was catalyzed by data sharing, open-source software\ndevelopment, as well as the organization of dedicated workshops led by a\ndiverse team of early career researchers. To this end, we argue that the\ngrowing excitement for brain gradients is the result of coordinated and\nconsistent efforts to build an inclusive community and can serve as a case in\npoint for future innovations and conceptual advances in neuroinformatics. We\nclose this perspective paper by discussing challenges for the continuous\nrefinement of neuroscientific theory, methodological innovation, and real-world\ntranslation to maintain our collective progress towards integrated models of\nbrain organization.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gradients of brain organization: Smooth sailing from methods development to user community\",\"authors\":\"Jessica Royer, Casey Paquola, Sofie L. Valk, Matthias Kirschner, Seok-Jun Hong, Bo-yong Park, Richard A. I. Bethlehem, Robert Leech, B. T. Thomas Yeo, Elizabeth Jefferies, Jonathan Smallwood, Daniel Margulies, Boris C. Bernhardt\",\"doi\":\"arxiv-2402.11055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multimodal neuroimaging grants a powerful in vivo window into the structure\\nand function of the human brain. Recent methodological and conceptual advances\\nhave enabled investigations of the interplay between large-scale spatial\\ntrends, or gradients, in brain structure and function, offering a framework to\\nunify principles of brain organization across multiple scales. Strong community\\nenthusiasm for these techniques has been instrumental in their widespread\\nadoption and implementation to answer key questions in neuroscience. Following\\na brief review of current literature on this framework, this perspective paper\\nwill highlight how pragmatic steps aiming to make gradient methods more\\naccessible to the community propelled these techniques to the forefront of\\nneuroscientific inquiry. More specifically, we will emphasize how interest for\\ngradient methods was catalyzed by data sharing, open-source software\\ndevelopment, as well as the organization of dedicated workshops led by a\\ndiverse team of early career researchers. To this end, we argue that the\\ngrowing excitement for brain gradients is the result of coordinated and\\nconsistent efforts to build an inclusive community and can serve as a case in\\npoint for future innovations and conceptual advances in neuroinformatics. We\\nclose this perspective paper by discussing challenges for the continuous\\nrefinement of neuroscientific theory, methodological innovation, and real-world\\ntranslation to maintain our collective progress towards integrated models of\\nbrain organization.\",\"PeriodicalId\":501219,\"journal\":{\"name\":\"arXiv - QuanBio - Other Quantitative Biology\",\"volume\":\"3 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Other Quantitative Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2402.11055\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Other Quantitative Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2402.11055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

多模态神经成像为了解人类大脑的结构和功能提供了一个强大的活体窗口。最近在方法论和概念上的进步使人们能够研究大脑结构和功能的大尺度空间趋势或梯度之间的相互作用,提供了一个框架来确定跨多个尺度的大脑组织原理。社会各界对这些技术的强烈热情有助于它们被广泛采用和实施,以回答神经科学中的关键问题。在简要回顾了有关该框架的现有文献之后,这篇视角论文将着重介绍旨在使梯度方法更容易为社会所接受的务实步骤是如何将这些技术推向神经科学探索的前沿的。更具体地说,我们将强调数据共享、开源软件开发以及由不同的早期职业研究人员团队领导的专门研讨会是如何促进人们对梯度方法的兴趣的。为此,我们认为,脑梯度研究的日益兴盛是建立一个包容性社区的协调和持续努力的结果,可以作为神经信息学未来创新和概念进步的一个案例。最后,我们讨论了神经科学理论的不断完善、方法论的创新和现实世界的转化所面临的挑战,以保持我们在脑组织综合模型方面的集体进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Gradients of brain organization: Smooth sailing from methods development to user community
Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends, or gradients, in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Opportunities and challenges of mRNA technologies in development of Dengue Virus Vaccine Compatibility studies of loquat scions with loquat and quince rootstocks Analysis of Potential Biases and Validity of Studies Using Multiverse Approaches to Assess the Impacts of Government Responses to Epidemics Advances in Nanoparticle-Based Targeted Drug Delivery Systems for Colorectal Cancer Therapy: A Review Unveiling Parkinson's Disease-like Changes Triggered by Spaceflight
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1