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R1加权连接组:用一种对髓磷脂敏感的测量方法补充脑网络。

The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure.

作者信息

Boshkovski Tommy, Kocarev Ljupco, Cohen-Adad Julien, Mišić Bratislav, Lehéricy Stéphane, Stikov Nikola, Mancini Matteo

机构信息

NeuroPoly Lab, Polytechnique Montreal, Montreal, QC, Canada.

Macedonian Academy of Sciences and Arts, Skopje, Macedonia.

出版信息

Netw Neurosci. 2021 Apr 27;5(2):358-372. doi: 10.1162/netn_a_00179. eCollection 2021.

Abstract

Myelin plays a crucial role in how well information travels between brain regions. Complementing the structural connectome, obtained with diffusion MRI tractography, with a myelin-sensitive measure could result in a more complete model of structural brain connectivity and give better insight into white-matter myeloarchitecture. In this work we weight the connectome by the longitudinal relaxation rate (R1), a measure sensitive to myelin, and then we assess its added value by comparing it with connectomes weighted by the number of streamlines (NOS). Our analysis reveals differences between the two connectomes both in the distribution of their weights and the modular organization. Additionally, the rank-based analysis shows that R1 can be used to separate transmodal regions (responsible for higher-order functions) from unimodal regions (responsible for low-order functions). Overall, the R1-weighted connectome provides a different perspective on structural connectivity taking into account white matter myeloarchitecture.

摘要

髓磷脂在大脑区域之间信息传递的顺畅程度方面起着至关重要的作用。用对髓磷脂敏感的测量方法补充通过扩散磁共振成像纤维束成像获得的结构连接组,可能会产生一个更完整的大脑结构连接模型,并能更好地洞察白质髓鞘结构。在这项工作中,我们用纵向弛豫率(R1)对连接组进行加权,R1是一种对髓磷脂敏感的测量方法,然后通过将其与按流线数量(NOS)加权的连接组进行比较来评估其附加值。我们的分析揭示了两个连接组在权重分布和模块化组织方面的差异。此外,基于秩的分析表明,R1可用于将跨模态区域(负责高阶功能)与单模态区域(负责低阶功能)区分开来。总体而言,R1加权连接组在考虑白质髓鞘结构的情况下,为结构连接提供了一个不同的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6fb3/8233108/9d4a0083fef0/netn-05-358-g001.jpg

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