ReviewCurrent opinion in neurology2022
Reproducibility and replicability in neuroimaging data analysis.
Review in Current opinion in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility.NeuroImage · 2023Pooled it
- Sleep quality is associated with default mode and salience network connectivity differently across age and sex.Neurobiology of aging · 2026Article
- Preserved topography, lateralization, selectivity, and functional connectivity of the language network in older brains.Nature communications · 2026Article
- An Interpretable Machine Learning Model for Predicting the Presence of Talaromycosis in HIV Patients Lacking Skin Lesions.Mycopathologia · 2026Article
- In silico models in oncology, neurology, and epidemiology: systems-level and multiscale perspectives.NPJ systems biology and applications · 2026Review
- Fusion of Multi-Task fMRI Data: Guided Solutions for IVA and Transposed IVA.Sensors (Basel, Switzerland) · 2026Article
- Advanced Neuroimaging and Emerging Systemic Therapies in Glioblastoma: Current Evidence and Future Directions.Biomedicines · 2025Review
- Time-Varying Spatial Propagation of Brain Networks in fMRI Data.Human brain mapping · 2025Article
- Open-source platforms to investigate analytical flexibility in neuroimaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Imaging-genomic spatial-modality attentive fusion for studying neuropsychiatric disorders.Human brain mapping · 2024Article
- Higher amplitudes of visual networks are associated with trait- but not state-depression.Psychological medicine · 2024Article
- Risk of intraoperative hemorrhage during cesarean scar ectopic pregnancy surgery: development and validation of an interpretable machine learning prediction model.EClinicalMedicine · 2024Article
- Multimodal active subspace analysis for computing assessment oriented subspaces from neuroimaging data.Journal of neuroscience methods · 2024Article
- A critical moment in machine learning in medicine: on reproducible and interpretable learning.Acta neurochirurgica · 2024Review
- Intra-V1 functional networks and classification of observed stimuli.Frontiers in neuroinformatics · 2024Article
- Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter.Frontiers in neurology · 2023Article
- Editorial: What the New White House Rules on Equitable Access Mean for the Neurosciences.Neuroinformatics · 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
2 authors.
Funding
Abstract
purpose of reviewMachine learning solutions are being increasingly used in the analysis of neuroimaging (NI) data, and as a result, there is an increase in the emphasis of the reproducibility and replicability of these data-driven solutions. Although this is a very positive trend, related terminology is often not properly defined, and more importantly, (computational) reproducibility that refers to obtaining consistent results using the same data and the same code is often disregarded. RECENT
findingsWe review the findings of a recent paper on the topic along with other relevant literature, and present two examples that demonstrate the importance of accounting for reproducibility in widely used software for NI data. SUMMARY: We note that reproducibility should be a first step in all NI data analyses including those focusing on replicability, and introduce available solutions for assessing reproducibility. We add the cautionary remark that when not taken into account, lack of reproducibility can significantly bias all subsequent analysis stages.
Indexed as
Identifiers
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.