ReviewFrontiers in neuroinformatics2018
Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience.
Review in Frontiers in neuroinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Modern techniques of teaching and learning in medical education: a descriptive literature review.MedEdPublish (2016) · 2021Pooled it
- Reproducibility in biomedical research.Nature medicine · 2026Review
- Enhanced beta power emerges from simulated parkinsonian primary motor cortex.NPJ Parkinson's disease · 2025Article
- Enhanced beta power emerges from simulated parkinsonian primary motor cortex.bioRxiv : the preprint server for biology · 2025Article
- Are Your Laboratory Data Reproducible? The Critical Role of Imprecision from Replicate Measurements to Clinical Decision-making.Annals of laboratory medicine · 2025Review
- Guidance for sharing computational models of neural stimulation: from project planning to publication.Journal of neural engineering · 2025Review
- Biophysical modelling of intrinsic cardiac nervous system neuronal electrophysiology based on single-cell transcriptomics.The Journal of physiology · 2025Article
- Quasistatic approximation in neuromodulation.Journal of neural engineering · 2024Review
- Influence of Chronic Forced Immobilization and Consumption of a High-Fat and High-Carbohydrate Diet Containing Cholesterol on Lipid and Cholesterol Metabolism in Male Wistar Rats.Bulletin of experimental biology and medicine · 2024Article
- Harmonizing AI governance regulations and neuroinformatics: perspectives on privacy and data sharing.Frontiers in neuroinformatics · 2024Article
- Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Assessing Model Calibration Workflows and Outcomes.Journal of biomechanical engineering · 2023Article
- Article
- Standards, dissemination, and best practices in systems biology.Current opinion in biotechnology · 2023Review
- Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action.International journal of environmental research and public health · 2023Article
- Modernizing the NEURON Simulator for Sustainability, Portability, and Performance.Frontiers in neuroinformatics · 2022Article
- Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: a software engineering perspective.NPJ systems biology and applications · 2021Article
- Theoretical Relationship Between Two Measures of Spike Synchrony: Correlation Index and Vector Strength.Frontiers in neuroscience · 2021Article
- Article
- Review
- Propagation of Pericentral Necrosis During Acetaminophen-Induced Liver Injury: Evidence for Early Interhepatocyte Communication and Information Exchange.Toxicological sciences : an official journal of the Society of Toxicology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Modeling and simulation in computational neuroscience is currently a research enterprise to better understand neural systems. It is not yet directly applicable to the problems of patients with brain disease. To be used for clinical applications, there must not only be considerable progress in the field but also a concerted effort to use best practices in order to demonstrate model credibility to regulatory bodies, to clinics and hospitals, to doctors, and to patients. In doing this for neuroscience, we can learn lessons from long-standing practices in other areas of simulation (aircraft, computer chips), from software engineering, and from other biomedical disciplines. In this manuscript, we introduce some basic concepts that will be important in the development of credible clinical neuroscience models: reproducibility and replicability; verification and validation; model configuration; and procedures and processes for credible mechanistic multiscale modeling. We also discuss how garnering strong community involvement can promote model credibility. Finally, in addition to direct usage with patients, we note the potential for simulation usage in the area of Simulation-Based Medical Education, an area which to date has been primarily reliant on physical models (mannequins) and scenario-based simulations rather than on numerical simulations.
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.