| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6033237 | NeuroImage | 2012 | 16 Pages |
Abstract
âºWe propose multivariate, data-driven method for removing physiological noise in fMRI. âºIdentifies artifact via autocorrelation, power spectrum and spatial reproducibility. âºSignificantly improves prediction and reproducibility of fMRI results. âºNoise shows subject/task-dependent dimensionality. âºNoise dimensionality correlated with respiratory and cardiac rate variability.
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Authors
Nathan W. Churchill, Grigori Yourganov, Robyn Spring, Peter M. Rasmussen, Wayne Lee, Jon E. Ween, Stephen C. Strother,