ArticleBrain connectivity2015
Using Edge Voxel Information to Improve Motion Regression for rs-fMRI Connectivity Studies.
Article in Brain connectivity, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
17 citing papers in PubMed.
- Quality assessment and control of unprocessed anatomical, functional and diffusion MRI of the human brain using MRIQC.Nature protocols · 2026Review
- Parallel processing chains span cytoarchitectures to organize association cortex.bioRxiv : the preprint server for biology · 2026Article
- Data-driven denoising in spinal cord fMRI with principal component analysis.bioRxiv : the preprint server for biology · 2025Article
- Interactions between functional networks in Parkinson's disease mild cognitive impairment.Scientific reports · 2023Article
- Quality control in resting-state fMRI: the benefits of visual inspection.Frontiers in neuroscience · 2023Article
- Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Article
- Integrative and Network-Specific Connectivity of the Basal Ganglia and Thalamus Defined in Individuals.Neuron · 2020Article
- A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum.NeuroImage · 2020Article
- Combining Prospective Acquisition CorrEction (PACE) with retrospective correction to reduce motion artifacts in resting state fMRI data.Brain and behavior · 2019Article
- On time delay estimation and sampling error in resting-state fMRI.NeuroImage · 2019Article
- Head motion: the dirty little secret of neuroimaging in psychiatryJournal of psychiatry & neuroscience : JPN · 2019Article
- Resting State fMRI: Going Through the Motions.Frontiers in neuroscience · 2019Review
- Methods for cleaning the BOLD fMRI signal.NeuroImage · 2017Review
- Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps.Brain structure & function · 2017Article
- An improved model of motion-related signal changes in fMRI.NeuroImage · 2017Article
- Data-driven denoising in spinal cord fMRI with principal component analysis.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Recent fMRI studies have outlined the critical impact of in-scanner head motion, particularly on estimates of functional connectivity. Common strategies to reduce the influence of motion include realignment as well as the inclusion of nuisance regressors, such as the 6 realignment parameters, their first derivatives, time-shifted versions of the realignment parameters, and the squared parameters. However, these regressors have limited success at noise reduction. We hypothesized that using nuisance regressors consisting of the principal components (PCs) of edge voxel time series would be better able to capture slice-specific and nonlinear signal changes, thus explaining more variance, improving data quality (i.e., lower DVARS and temporal SNR), and reducing the effect of motion on default-mode network connectivity. Functional MRI data from 22 healthy adult subjects were preprocessed using typical motion regression approaches as well as nuisance regression derived from edge voxel time courses. Results were evaluated in the presence and absence of both global signal regression and motion censoring. Nuisance regressors derived from signal intensity time courses at the edge of the brain significantly improved motion correction compared to using only the realignment parameters and their derivatives. Of the models tested, only the edge voxel regression models were able to eliminate significant differences in default-mode network connectivity between high- and low-motion subjects regardless of the use of global signal regression or censoring.
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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.