Name
Abstract | ||
|---|---|---|
The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.neuroimage.2017.05.031 | NeuroImage |
Keywords | Field | DocType |
FMRI,Noise sources,Physiological noise,Motion,General linear model | Reprint,Functional magnetic resonance imaging,Psychology,Cognitive psychology,Brain activity and meditation,Communication noise | Journal |
Volume | ISSN | Citations |
154 | 1053-8119 | 1 |
PageRank | References | Authors |
0.36 | 51 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas T Liu | 1 | 1022 | 76.03 |