Visual inspection of independent components: defining a procedure for artifact removal from fMRI data.

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.

journal_name

J Neurosci Methods

authors

Kelly RE Jr,Alexopoulos GS,Wang Z,Gunning FM,Murphy CF,Morimoto SS,Kanellopoulos D,Jia Z,Lim KO,Hoptman MJ

doi

10.1016/j.jneumeth.2010.03.028

subject

Has Abstract

pub_date

2010-06-15 00:00:00

pages

233-45

issue

2

eissn

0165-0270

issn

1872-678X

pii

S0165-0270(10)00162-7

journal_volume

189

pub_type

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