Resting-State fMRI: A Review of Methods and Clinical Applications
Abstract
SUMMARY: 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.
Abbreviations
- BOLD
- blood oxygen level–dependent
- DMN
- default mode network
- ICA
- independent component analysis
- RS-fMRI
- resting-state fMRI
- RSN
- resting-state network
- © 2013 American Society of Neuroradiology
Indicates open access to non-subscribers at www.ajnr.org
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