Mallinckrodt Institute of Radiology.
AJNR Am J Neuroradiol. 2013 Oct;34(10):1866-72. doi: 10.3174/ajnr.A3263. Epub 2012 Aug 30.
Resting-state fMRI measures spontaneous low-frequency fluctuations in the BOLD signal to investigate the functional architecture of the brain. Application of this technique has allowed the identification of various RSNs, or spatially distinct areas of the brain that demonstrate synchronous BOLD fluctuations at rest. Various methods exist for analyzing resting-state data, including seed-based approaches, independent component analysis, graph methods, clustering algorithms, neural networks, and pattern classifiers. Clinical applications of resting-state fMRI are at an early stage of development. However, its use in presurgical planning for patients with brain tumor and epilepsy demonstrates early promise, and the technique may have a future role in providing diagnostic and prognostic information for neurologic and psychiatric diseases.
静息态 fMRI 通过测量血氧水平依赖信号的自发低频波动来研究大脑的功能结构。这项技术的应用使得能够识别各种 RSN，即大脑中在静息状态下表现出同步血氧水平依赖波动的不同空间区域。存在多种用于分析静息态数据的方法，包括基于种子的方法、独立成分分析、图方法、聚类算法、神经网络和模式分类器。静息态 fMRI 的临床应用仍处于早期发展阶段。然而，它在脑肿瘤和癫痫患者术前计划中的应用显示出了早期的前景，该技术可能在为神经和精神疾病提供诊断和预后信息方面发挥未来作用。
