Publication Type Academic Article
Authors Kelly R, Alexopoulos G, Wang Z, Gunning F, Murphy C, Morimoto S, Kanellopoulos D, Jia Z, Lim K, Hoptman M
Journal J Neurosci Methods
Volume 189
Issue 2
Pagination 233-45
Date Published 04/08/2010
ISSN 1872-678X
Keywords Artifacts, Brain Mapping, Image Processing, Computer-Assisted, Magnetic Resonance Imaging
Abstract Artifacts in functional magnetic resonance imaging (fMRI) data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis' demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to which automated labeling methods are compared. However, detailed descriptions of methods for visual inspection of ICs are lacking in the literature. Here we describe the details of, and the rationale for, an operationalized fMRI data denoising procedure that involves visual inspection of ICs (96% inter-rater agreement). We estimate that dozens of subjects/sessions can be processed within a few hours using the described method of visual inspection. Our hope is that continued scientific discussion of and testing of visual inspection methods will lead to the development of improved, cost-effective fMRI denoising procedures.
DOI 10.1016/j.jneumeth.2010.03.028
PubMed ID 20381530
PubMed Central ID PMC3299198
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