ArticleNeuroImage2015
Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure.
Article in NeuroImage, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
87 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Aberrant cortical-subcortical-cerebellar connectivity in resting-state fMRI as an imaging marker of schizophrenia and psychosis: a systematic review of data-driven whole-brain functional connectivity analyses.Frontiers in neuroimaging · 2025Pooled it
- Modulation of simultaneously collected hemodynamic and electrophysiological functional connectivity by ketamine and midazolam.Human brain mapping · 2020Trial
- Physical characteristics not psychological state or trait characteristics predict motion during resting state fMRI.Scientific reports · 2019Trial
- Eigenvalue Signatures Reveal Residual Motion Effects Across Resting-State fMRI Denoising Strategies.bioRxiv : the preprint server for biology · 2026Article
- Toward multimodal MRI biomarkers of PTSD: functional and structural connectivity signatures in WTC responders.medRxiv : the preprint server for health sciences · 2026Article
- Fetal and postnatal metal metabolism-related changes in brain function are associated with childhood behavioral deficits.Science advances · 2026Article
- Cross-sectional observational study evaluating social brain health in HIV using a research domain criteria-based approach: a protocol.BMJ open · 2026Article
- Human fMRI at 11.7T: Assessing feasibility, stability, and reliability on the Iseult scanner.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Functional MRI signals as fast as 1Hz are coupled to brain states and predict spontaneous neural activity.bioRxiv : the preprint server for biology · 2025Article
- Brainwide hemodynamics predict EEG neural rhythms across sleep and wakefulness in humans.PLoS computational biology · 2025Article
- Review
- Brainwide hemodynamics predict EEG neural rhythms across sleep and wakefulness in humans.bioRxiv : the preprint server for biology · 2025Article
- Correction of Physiological Artifacts in Multi-Echo fMRI Data-Evaluation of Possible RETROICOR Implementations.Human brain mapping · 2025Article
- COVID-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study.Translational psychiatry · 2024Article
- A standardized image processing and data quality platform for rodent fMRI.Nature communications · 2024Article
- The Role of Subgenual Resting-State Connectivity Networks in Predicting Prognosis in Major Depressive Disorder.Biological psychiatry global open science · 2024Article
- Diverse adolescents' transcendent thinking predicts young adult psychosocial outcomes via brain network development.Scientific reports · 2024Article
- Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility.Frontiers in psychiatry · 2024Article
- Functional changes in neural mechanisms underlying post-traumatic stress disorder in World Trade Center responders.Translational psychiatry · 2023Article
- State-of-the-art imaging of neuromodulatory subcortical systems in aging and Alzheimer's disease: Challenges and opportunities.Neuroscience and biobehavioral reviews · 2023Review
27 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.