Data_Sheet_1_A systematic review of the relationship between magnetic resonance imaging based resting-state and structural networks in the rodent brain.docx

Recent developments in rodent brain imaging have enabled translational characterization of functional and structural connectivity at the whole brain level in vivo. Nevertheless, fundamental questions about the link between structural and functional networks remain unsolved. In this review, we systematically searched for experimental studies in rodents investigating both structural and functional network measures, including studies correlating functional connectivity using resting-state functional MRI with diffusion tensor imaging or viral tracing data. We aimed to answer whether functional networks reflect the architecture of the structural connectome, how this reciprocal relationship changes throughout a disease, how structural and functional changes relate to each other, and whether changes follow the same timeline. We present the knowledge derived exclusively from studies that included in vivo imaging of functional and structural networks. The limited number of available reports makes it difficult to draw general conclusions besides finding a spatial and temporal decoupling between structural and functional networks during brain disease. Data suggest that when overcoming the currently limited evidence through future studies with combined imaging in various disease models, it will be possible to explore the interaction between both network systems as a disease or recovery biomarker.

近年来，啮齿类动物脑成像（rodent brain imaging）领域的最新进展已实现全脑水平活体状态下功能与结构连接的转化表征。然而，有关结构与功能网络间关联的核心问题仍未得到解决。在本综述中，我们系统检索了同时探究结构与功能网络指标的啮齿类动物实验研究，涵盖了将静息态功能磁共振成像（resting-state functional MRI）获取的功能连接与弥散张量成像（diffusion tensor imaging）或病毒示踪数据进行关联分析的相关研究。本综述旨在解答四类核心问题：功能网络是否能够反映结构连接组（structural connectome）的架构？这种相互关联在疾病进程中会发生何种动态变化？结构与功能的改变之间存在何种内在联系？以及上述改变是否遵循统一的时间进程？本文所呈现的知识，全部源自纳入了功能与结构网络活体成像的相关研究。当前可用的相关报道数量有限，因此除了明确观察到脑疾病期间结构与功能网络存在时空解耦现象外，难以得出普适性结论。现有数据提示，若未来通过在多种疾病模型中开展联合成像研究以弥补当前证据不足的局限，将有望探索这两类网络系统的相互作用机制，并将其作为疾病进程或康复过程的生物标志物（biomarker）。