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brainlife.io: A decentralized and open source cloud platform to support neuroscience research

Authors :
Hayashi, Soichi
Caron, Bradley A.
Heinsfeld, Anibal Sólon
Vinci-Booher, Sophia
McPherson, Brent
Bullock, Daniel N.
Bertò, Giulia
Niso, Guiomar
Hanekamp, Sandra
Levitas, Daniel
Ray, Kimberly
MacKenzie, Anne
Kitchell, Lindsey
Leong, Josiah K.
Nascimento-Silva, Filipi
Koudoro, Serge
Willis, Hanna
Jolly, Jasleen K.
Pisner, Derek
Zuidema, Taylor R.
Kurzawski, Jan W.
Mikellidou, Kyriaki
Bussalb, Aurore
Rorden, Christopher
Victory, Conner
Bhatia, Dheeraj
Aydogan, Dogu Baran
Yeh, Fang-Cheng F.
Delogu, Franco
Guaje, Javier
Veraart, Jelle
Bollman, Steffen
Stewart, Ashley
Fischer, Jeremy
Faskowitz, Joshua
Chaumon, Maximilien
Fabrega, Ricardo
Hunt, David
McKee, Shawn
Brown, Shawn T.
Heyman, Stephanie
Iacovella, Vittorio
Mejia, Amanda F.
Marinazzo, Daniele
Craddock, R. Cameron
Olivetti, Emanuele
Hanson, Jamie L.
Avesani, Paolo
Garyfallidis, Eleftherios
Stanzione, Dan
Carson, James
Henschel, Robert
Hancock, David Y.
Stewart, Craig A.
Schnyer, David
Eke, Damian O.
Poldrack, Russell A.
George, Nathalie
Bridge, Holly
Sani, Ilaria
Freiwald, Winrich A.
Puce, Aina
Port, Nicholas L.
Pestilli, Franco
Publication Year :
2023

Abstract

Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR (Findable, Accessible, Interoperabile, and Reusable) data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2306.02183
Document Type :
Working Paper
Full Text :
https://doi.org/10.1038/s41592-024-02237-2