The NARPS Open Pipelines project

Table of contents

• Project presentation
• Getting Started
  • Contents overview
  • Installation
  • Contributing
• References
• Funding

Project presentation

Neuroimaging workflows are highly flexible, leaving researchers with multiple possible options to analyze a dataset (Carp, 2012). However, different analytical choices can cause variation in the results (Botvinik-Nezer et al., 2020), leading to what was called a "vibration of effects" (Ioannidis, 2008) also known as analytical variability.

The goal of the NARPS Open Pipelines project is to create a codebase reproducing the 70 pipelines of the NARPS project (Botvinik-Nezer et al., 2020) and share this as an open resource for the community.

To perform the reproduction, we are lucky to be able to use the descriptions provided by the teams. We also created a shared spreadsheet that can be used to add comments on pipelines (e.g.: identify the ones that are not reproducible with NiPype).

🚦 Lastly, please find here in the project's wiki a dashboard to see pipelines work progresses at first glance.

Getting Started

Contents overview

• 🐍 📦 narps_open/ contains the Python package with all the pipelines logic.
• 🧠 data/ contains data that is used by the pipelines, as well as the (intermediate or final) results data. Instructions to download data are available in INSTALL.md.
• 📘 docs/ contains the documentation for the project. Start browsing it with the entry point docs/README.md
• 📙 examples/ contains notebooks examples to launch of the reproduced pipelines.
• 🔬 tests/ contains the tests of the narps_open package.

Installation

To get the pipelines running, please follow the installation steps in INSTALL.md

Contributing

👋 Any help is welcome ! Follow the guidelines in CONTRIBUTING.md if you wish to get involved !

References

1. Botvinik-Nezer, R. et al. (2020), ‘Variability in the analysis of a single neuroimaging dataset by many teams’, Nature.
2. Carp, J. et al. (2012), ‘On the Plurality of (Methodological) Worlds: Estimating the Analytic Flexibility of fMRI Experiments’, Frontiers in Neuroscience.
3. Gorgolewski, K.J. et al. (2015), ‘NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain’ Frontiers in Neuroinformatics.
4. Ioannidis, J.P.A. (2008), ‘Why Most Discovered True Associations Are Inflated’, Epidemiology.

Funding

This project is supported by Région Bretagne (Boost MIND).

Credits

This project is developed in the Empenn team by Boris Clenet, Elodie Germani, Jeremy Lefort-Besnard and Camille Maumet with contributions by Rémi Gau.

In addition, this project was presented and received contributions during the following events:

• OHBM Brainhack 2022 (June 2022): Elodie Germani, Arshitha Basavaraj, Trang Cao, Rémi Gau, Anna Menacher, Camille Maumet.
• e-ReproNim FENS NENS Cluster Brainhack (June 2023) : Liz Bushby, Boris Clénet, Michael Dayan, Aimee Westbrook.
• OHBM Brainhack 2023 (July 2023): Arshitha Basavaraj, Boris Clénet, Rémi Gau, Élodie Germani, Yaroslav Halchenko, Camille Maumet, Paul Taylor.
• ORIGAMI lab hackathon (Sept 2023):