Potential pitfalls when denoising resting state fMRI data using nuisance regression
(2016)
Journal Article
Bright, M. G., Tench, C. R., & Murphy, K. (2017). Potential pitfalls when denoising resting state fMRI data using nuisance regression. NeuroImage, 154, 159-168. https://doi.org/10.1016/j.neuroimage.2016.12.027
In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through n... Read More about Potential pitfalls when denoising resting state fMRI data using nuisance regression.