人脑在超高场下的多模态精确核磁共振成像。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Donna Gift Cabalo, Ilana Ruth Leppert, Risavarshni Thevakumaran, Jordan DeKraker, Youngeun Hwang, Jessica Royer, Valeria Kebets, Shahin Tavakol, Yezhou Wang, Yigu Zhou, Oualid Benkarim, Nicole Eichert, Casey Paquola, Julien Doyon, Christine Lucas Tardif, David Rudko, Jonathan Smallwood, Raul Rodriguez-Cruces, Boris C Bernhardt
{"title":"人脑在超高场下的多模态精确核磁共振成像。","authors":"Donna Gift Cabalo, Ilana Ruth Leppert, Risavarshni Thevakumaran, Jordan DeKraker, Youngeun Hwang, Jessica Royer, Valeria Kebets, Shahin Tavakol, Yezhou Wang, Yigu Zhou, Oualid Benkarim, Nicole Eichert, Casey Paquola, Julien Doyon, Christine Lucas Tardif, David Rudko, Jonathan Smallwood, Raul Rodriguez-Cruces, Boris C Bernhardt","doi":"10.1038/s41597-025-04863-7","DOIUrl":null,"url":null,"abstract":"<p><p>Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7 T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply \"gradients\" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"526"},"PeriodicalIF":6.9000,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954990/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multimodal precision MRI of the individual human brain at ultra-high fields.\",\"authors\":\"Donna Gift Cabalo, Ilana Ruth Leppert, Risavarshni Thevakumaran, Jordan DeKraker, Youngeun Hwang, Jessica Royer, Valeria Kebets, Shahin Tavakol, Yezhou Wang, Yigu Zhou, Oualid Benkarim, Nicole Eichert, Casey Paquola, Julien Doyon, Christine Lucas Tardif, David Rudko, Jonathan Smallwood, Raul Rodriguez-Cruces, Boris C Bernhardt\",\"doi\":\"10.1038/s41597-025-04863-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7 T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply \\\"gradients\\\" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"12 1\",\"pages\":\"526\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954990/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-025-04863-7\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-04863-7","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

多模态神经成像,特别是磁共振成像(MRI),可以跨多个尺度对人脑结构和功能进行无创检查。精确的神经成像建立在这个基础之上,能够在单个个体中以高保真度绘制大脑结构、功能和连接模式。高场MRI在7特斯拉(T)或更高的磁场强度下工作,提高了信噪比,并为获得空间分辨率开辟了可能性。在这里,我们共享了一个多模态精确神经成像和连接组学(PNI) 7 T MRI数据集。10名健康个体接受了全面的MRI方案,包括T1松弛测量,磁化转移成像,T2*加权成像,弥散MRI和多状态功能MRI范式,在三个成像过程中汇总。除了匿名的原始MRI数据外,我们还从不同的方式跨多个分割尺度发布了皮质范围内的连接体,并提供了“梯度”,以紧凑地表征皮层组织的空间模式。我们的精确MRI数据集将促进我们对个体人脑结构-功能关系的理解,并通过开放科学框架公开提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multimodal precision MRI of the individual human brain at ultra-high fields.

Multimodal precision MRI of the individual human brain at ultra-high fields.

Multimodal precision MRI of the individual human brain at ultra-high fields.

Multimodal precision MRI of the individual human brain at ultra-high fields.

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7 T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

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
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信