Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

静息状态功能磁共振成像 (rs-fMRI) 是基于血氧水平依赖 (BOLD) 信号的自发波动，这种波动同时发生在不同的大脑区域，而受试者无需执行明确的任务。rs-fMRI 信号的低频振荡表明大脑（大脑网络）中可能与潜在的神经活动有关的内在时空组织。在这篇评论文章中，我们简要描述了当前的 rs-fMRI 数据采集技术，从最常见的静息状态采集策略方法到最近对专用硬件和超高场的研究。接下来讨论允许非常快速采集或多个回波的特定序列。然后，我们考虑对 BOLD 信号的特定部分加权的采集方法，如脑血流量 (CBF) 或容量 (CBV)，如何提供更多空间特定的网络信息。这些方法正在与常用的 BOLD 加权收购一起开发。最后，讨论了 rs-fMRI 在具有挑战性的区域（例如新皮质中的椎板）和大面积皮质下白质区域内的网络的具体应用。最后，我们对静息状态 fMRI 的一系列典型应用的采集策略提出了建议。讨论了 rs-fMRI 在具有挑战性的区域（例如新皮质中的椎板）和大面积皮质下白质区域内的网络的具体应用。最后，我们对静息状态 fMRI 的一系列典型应用的采集策略提出了建议。讨论了 rs-fMRI 在具有挑战性的区域（例如新皮质中的椎板）和大面积皮质下白质区域内的网络的具体应用。最后，我们对静息状态 fMRI 的一系列典型应用的采集策略提出了建议。