ReviewNeuroImage2017
Prospective motion correction in functional MRI.
Review in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
58 citing papers in PubMed.
- Servo Navigation and Phase Equalization Enhanced by Run-Time Stabilization (PEERS) for 3D EPI Time Series.Magnetic resonance in medicine · 2026Article
- Prospective motion correction with data reacquisition based on fat navigators for T1-weighted brain MRI at 3T.Medical & biological engineering & computing · 2026Article
- Simultaneous Volumetric T1 and T2 Mapping With Blood- and Fat-Suppression in Abdominal Aortic Aneurysms.Magnetic resonance in medicine · 2026Article
- Article
- Human fMRI at 11.7T: Assessing feasibility, stability, and reliability on the Iseult scanner.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- The Bias Associated with Movement-related Data Exclusion in Psychosis MRI Research.Indian journal of psychological medicine · 2025Article
- Voxel Volume Overlap: Voxel-Size Sensitive Indicators of Subject Motion in Functional MRI.Human brain mapping · 2025Article
- The Expanding Frontier: The Role of Artificial Intelligence in Pediatric Neuroradiology.Children (Basel, Switzerland) · 2025Review
- Prospective 3D Fat Navigator (FatNav) motion correction for 7T Terra MRI.NMR in biomedicine · 2025Article
- Balancing Data Quality and Bias: Investigating Functional Connectivity Exclusions in the Adolescent Brain Cognitive Development℠ (ABCD Study) Across Quality Control Pathways.Human brain mapping · 2025Article
- A deep neural network for adaptive spatial smoothing of task fMRI data.Frontiers in neuroimaging · 2025Article
- The German research consortium for the study of bipolar disorder (BipoLife): a quality assurance protocol for MR neuroimaging data.International journal of bipolar disorders · 2024Article
- Test Platform for Developing New Optical Position Tracking Technology towards Improved Head Motion Correction in Magnetic Resonance Imaging.Sensors (Basel, Switzerland) · 2024Article
- Advancements in MR hardware systems and magnetic field control: BPsychoradiology · 2024Review
- Improving motion robustness of 3D MR fingerprinting with a fat navigator.Magnetic resonance in medicine · 2023Article
- Prediction of motion induced magnetic fields for human brain MRI at 3 T.Magma (New York, N.Y.) · 2023Article
- Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States.Brain topography · 2023Article
- Systematic evaluation of head motion on resting-state functional connectivity MRI in the neonate.Human brain mapping · 2023Article
- Germany's journey toward 14 Tesla human magnetic resonance.Magma (New York, N.Y.) · 2023Review
- HALO: A software tool for real-time head alignment in the MR scanner.Magnetic resonance in medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Due to the intrinsic low sensitivity of BOLD-fMRI long scanning is required. Subject motion during fMRI scans reduces statistical significance of the activation maps and increases the prevalence of false activations. Motion correction is therefore an essential tool for a successful fMRI data analysis. Retrospective motion correction techniques are now commonplace and are incorporated into a wide range of fMRI analysis toolboxes. These techniques are advantageous due to robustness, sequence independence and have minimal impact on the fMRI study setup. Retrospective techniques however, do not provide an accurate intra-volume correction, nor can these techniques correct for the spin-history effects. The application of prospective motion correction in fMRI appears to be effective in reducing false positives and increasing sensitivity when compared to retrospective techniques, particularly in the cases of substantial motion. Especially advantageous in this regard is the combination of prospective motion correction with dynamic distortion correction. Nevertheless, none of the recent methods are able to recover activations in presence of motion that are comparable to no-motion conditions, which motivates further research in the area of adaptive dynamic imaging.
Indexed as
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What OpenQuestion holds
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.