ArticleImaging neuroscience (Cambridge, Mass.)2025
Challenging the status quo: A guide to open and reproducible neuroimaging for early career researchers.
Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Precision neurodiversity: personalized brain network architecture as a window into cognitive variability.Frontiers in human neuroscience · 2025Review
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
No grant is acknowledged in the PubMed record.
Abstract
In the last decade, neuroimaging research has seen a proliferation of open tools, platforms, and standards aimed at addressing the reproducibility crisis in the field. The growing awareness on this topic is bringing about a cultural shift in the scientific community, especially among early career researchers (ECRs). As members of this demographic, we can attest to the fact that the adoption of these new tools and practices remains a challenge. This work aims to provide a practical guide for ECRs to navigate the expanding landscape of the open-science resources and make proactive decisions for their research workflows dealing with large, multiple datasets. From our own experience, we describe the common hurdles faced in typical research workflow and provide a set of solutions that could serve as a starting point for researchers looking for practical tools and protocols. Through a hypothetical scenario, we walk through the steps of curating, processing, harmonizing, and publishing a dataset while describing the tools and practices helpful for adopting FAIR (findable, accessible, interoperable, and reusable) principles. We hope this guide can help ECRs and others to simplify their daily research life as we all strive towards more open, reproducible, and translational neuroscience research.
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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.