# ReproNim: A Center for Reproducible Neuroimaging Computation

> **NIH NIH P41** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2021 · $180,258

## Abstract

SUMMARY
Our proposed NCBIB resource, ReproNim: A Center for Reproducible Neuroimaging Computation, seeks
to continue to drive a shift in the way neuroimaging research is performed and reported. In the first award
period, we have successfully created a substantial set of tools, developed best practices and trained a cadre of
users that improves the baseline reproducibility of many studies. But there is more to do. Through the
continued development and implementation of technology that supports more efficiency and effectiveness for
more users, we extend our comprehensive set of data management, analysis and utilization frameworks in
support of both basic research and clinical activities. Our overarching goal is to improve the reproducibility
of neuroimaging science and extend the value of our national investment in neuroimaging research, while
making the process easier and more efficient for investigators. Reproducibility is critical because the
current literature is fraught with published results that are due to mistakes (occasionally misconduct); or turn
out to be false positives (contributed to by the lack of statistical power). More importantly, given the current
publication system, it is exceedingly difficult to discern between false positive and true positive finding as data
is hard to aggregate, and exact methods are hard to replicate.
In this Administration Core, we seek to continue to seamlessly and efficiently administer the overall
operations of the Center. To accomplish this, we will: 1) Provide overall management of the day-to-day
operations of the Center; 2) Provide continuous self-monitoring and external verification of our progress and
direction; and 3) Promote our technological developments with a voice that is heard within the national and
international neuroimaging, neuroinformatics and reproducibility research communities. We will work in
partnership with the other TR&D projects and the Collaborative and Service Project users and the Training and
Dissemination Core to foster knowledge of and use of the reproducible framework in the neuroimaging
research community.

## Key facts

- **NIH application ID:** 10334134
- **Project number:** 2P41EB019936-06A1
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** David Nelson Kennedy
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $180,258
- **Award type:** 2
- **Project period:** 2016-04-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10334134

## Citation

> US National Institutes of Health, RePORTER application 10334134, ReproNim: A Center for Reproducible Neuroimaging Computation (2P41EB019936-06A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10334134. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*