ArticleComputational brain & behavior2019
The importance of standards for sharing of computational models and data.
Article in Computational brain & behavior, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Development of a standardized intracranial vessel model from 3D time-of-flight magnetic resonance angiography data of the SHIP cohort.Neuroradiology · 2026Article
- The Virtual Brain Ontology: A Digital Knowledge Framework for Reproducible Brain Network Modeling.bioRxiv : the preprint server for biology · 2025Article
- Guidance for sharing computational models of neural stimulation: from project planning to publication.Journal of neural engineering · 2025Review
- The past, present, and future of the brain imaging data structure (BIDS).Imaging neuroscience (Cambridge, Mass.) · 2024Review
- Article
- Integrating model development across computational neuroscience, cognitive science, and machine learning.Neuron · 2023Article
- Article
- Data management strategy for a collaborative research center.GigaScience · 2022Article
- Review
- Editorial: 2021, A New Chapter.Computational psychiatry (Cambridge, Mass.) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
The Target Article by Lee et al. (2019) highlights the ways in which ongoing concerns about research reproducibility extend to model-based approaches in cognitive science. Whereas Lee et al. focus primarily on the importance of research practices to improve model robustness, we propose that the transparent sharing of model specifications, including their inputs and outputs, is also essential to improving the reproducibility of model-based analyses. We outline an ongoing effort (within the context of the Brain Imaging Data Structure community) to develop standards for the sharing of the structure of computational models and their outputs.
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.