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Resting-state fMRI confounds and cleanup
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Journal Article
Resting-state fMRI confounds and cleanup
2013
Overview
The goal of resting-state functional magnetic resonance imaging (fMRI) is to investigate the brain's functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of fMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state fMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state fMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state fMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline.
•Resting-state fMRI measures temporal similarity between BOLD signals.•Confounds can arise that affect the BOLD signals leading to spurious results.•Motion, cardiac/respiration, arterial CO2 concentration & blood pressure are sources.•Techniques to remove resting-state fMRI confounds are reviewed.•Noise correction is an essential step for resting-state fMRI analyses.
Publisher
Elsevier Inc,Elsevier Limited
