Resting-state fMRI confounds and cleanup
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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.
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Concerns that some patterns of spatially-extended spontaneous signals may be of non-neural physiological origin are increasingly being addressed.
“Although there has been concern that some patterns of spatially-extended spontaneous signals may be of non-neural physiological origin, these concerns are increasingly being addressed [9].”
From Functional connectomics from resting-state fMRI (2013) · cites this paper as [9]
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- Authors
- Murphy, K., Birn, R. M., & Bandettini, P. A.
- Affiliations
- Cardiff University (GB)
- University of Wisconsin–Madison (US)
- National Institutes of Health (US)
- Corresponding author
- Murphy, Kevin
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Pages
- 349-359
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3720818
- OpenAlex
- W2049325056
- Cited by
- 666
- References
- 127
- Citations by year
- 2026: 21 · 2025: 48 · 2024: 32 · 2023: 50 · 2022: 37 · 2021: 68 · 2020: 56 · 2019: 72 · 2018: 70 · 2017: 52 · 2016: 68 · 2015: 45 · 2014: 35 · 2013: 10
- FWCI
- 28.77
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Funders
- Wellcome Trust Research Career Development Fellowship
- NIH (RC1MH090912)
- Health Emotions Research Institute
- National Institute of Mental Health Intramural Research Program
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- resting-state fMRI, confounds, functional connectivity, BOLD signal, motion artifacts, arterial carbon dioxide, cerebral autoregulation, vasomotion
- MeSH terms
- Animals, Blood Flow Velocity, Brain, Cerebrovascular Circulation, Humans, Image Enhancement, Magnetic Resonance Imaging, Models, Anatomic, Models, Neurological, Nerve Net, Oxygen, Artifacts, Connectome
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