Bajic Dusica, Craig Michael M, Mongerson Chandler R L, Borsook David, Becerra Lino
Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States.
Center for Pain and the Brain, Boston Children's Hospital, Boston, MA, United States.
Front Neurosci. 2017 Dec 12;11:685. doi: 10.3389/fnins.2017.00685. eCollection 2017.
Rodent models have opened the door to a better understanding of the neurobiology of brain disorders and increased our ability to evaluate novel treatments. Resting-state functional magnetic resonance imaging (rs-fMRI) allows for exploration of large-scale brain networks with high spatial resolution. Its application in rodents affords researchers a powerful translational tool to directly assess/explore the effects of various pharmacological, lesion, and/or disease states on known neural circuits within highly controlled settings. Integration of animal and human research at the molecular-, systems-, and behavioral-levels using diverse neuroimaging techniques empowers more robust interrogations of abnormal/ pathological processes, critical for evolving our understanding of neuroscience. We present a comprehensive protocol to evaluate resting-state brain networks using Independent Component Analysis (ICA) in rodent model. Specifically, we begin with a brief review of the physiological basis for rs-fMRI technique and overview of rs-fMRI studies in rodents to date, following which we provide a robust step-by-step approach for rs-fMRI investigation including data collection, computational preprocessing, and brain network analysis. Pipelines are interwoven with underlying theory behind each step and summarized methodological considerations, such as alternative methods available and current consensus in the literature for optimal results. The presented protocol is designed in such a way that investigators without previous knowledge in the field can implement the analysis and obtain viable results that reliably detect significant differences in functional connectivity between experimental groups. Our goal is to empower researchers to implement rs-fMRI in their respective fields by incorporating technical considerations to date into a workable methodological framework.
啮齿动物模型为更好地理解脑部疾病的神经生物学打开了大门，并提高了我们评估新疗法的能力。静息态功能磁共振成像（rs-fMRI）能够以高空间分辨率探索大规模脑网络。其在啮齿动物中的应用为研究人员提供了一个强大的转化工具，可在高度可控的环境中直接评估/探索各种药理学、损伤和/或疾病状态对已知神经回路的影响。利用多种神经成像技术在分子、系统和行为水平上整合动物和人类研究，能够更有力地探究异常/病理过程，这对于深化我们对神经科学的理解至关重要。我们提出了一种在啮齿动物模型中使用独立成分分析（ICA）评估静息态脑网络的综合方案。具体而言，我们首先简要回顾rs-fMRI技术的生理基础以及迄今为止啮齿动物中rs-fMRI研究的概况，随后我们提供一种用于rs-fMRI研究的稳健的逐步方法，包括数据收集、计算预处理和脑网络分析。各个步骤都穿插着其背后的基础理论，并总结了方法学上的考虑因素，例如可用的替代方法以及文献中关于获得最佳结果的当前共识。所提出的方案设计得使该领域以前没有相关知识的研究人员也能够实施分析并获得可行的结果，可靠地检测实验组之间功能连接性的显著差异。我们的目标是通过将迄今为止的技术考虑因素纳入一个可行的方法框架，使研究人员能够在各自领域中实施rs-fMRI。
