An online platform for reproducible neuroscience.

How does it work?


Projects allow you to manage data, processing and results. Share Projects privately with collaborators or publicly with the community. maps data files to registered Datatypes, allowing Apps to interoperate.

Data can be uploaded using a web browser or the Brainlife CLI for bulk / BIDS upload.

Run App

See Apps for publicly registered Apps. Use Process page to store stage input datasets and data derivatives generated by running the Apps.

You can also quickly execute App directly from the App detail page. more

Bulk Processing

Our unique analysis management mechanism (pipeline) allows easy submission and monitoring of thousands of analyses. Apps are modular and each subject is processed independently. This leads to a high scalability, and makes Big Data ready.


Each datatype provides a set of visualizers for quick quality control. We support both web based and native visualizers, such as fsleyes, freeview, that are streamed directly from our GPU enabled VMs.

If you are a developer of a visualization tool, we can make it come alive by allowing users to launch your apps on any dataset hosted on Brainlife.

Data Provenance keeps track of the history of each dataset. It preserves input and output data files, Apps versions and configuration parameters as well as the computer resource used to generate the dataset.

You can count on to make sure your scientific results are reproducible.


Publish your full workflow, data, derivaties along with all the Apps used in a project with innovative publication method. A single Digital Object Identifyier (DOI) can be assigned to a full-record in a Project. publications are archived securely on a secure tape archive for long term preservation.

Brainlife is for everyone!

Brainlife reaches out beyond neuroscience experts. We've made sure that our UI and Apps can be used by non-neuroscentists by providing detailed information about each App with good default parameters that should work across a wide range of input datasets.


Students can quickly get started and learn about key concepts of brainimage data analysis. Brainlife can lower technical barriers that often impede an effective learning process.

Computer Scientists

Computer scientists and engineers can focus on developing new algorithms and new computing methods without having to learn the entire neuroimaging preprocessing steps.

Data Scientists

Statisticians and data scientists can use available datasets and data derivatives to gather new insights into individuality and variability in human populations.

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Neuroscience is engaging at the forefront of science by dissolving disciplinary boundaries and promoting transdisciplinary research. This process can facilitate discovery by convergent efforts from theoretical, experimental and cognitive neuroscience, as well as computer science and engineering.

To assure the success of this process, the current lack of established mechanisms to promote open sharing data, software and scientific results must be overcome. Promoting open software and data sharing has become paramount to addressing the problem of scientific reproducibility.

We address challenges to neuroscience open sharing and reproducibility by providing integrative mechanisms for publishing data, and algorithms while embedding them with computing resources to impact multiple scientific communities.

   .. seamless public access to data, computing, and reproducible algorithms, while promoting code sharing and upcycling the long tail of neuroscience data. - NSF BCS-1734853

A global multidisciplinary collaboration

Sixty-six collaborators from global scientific communities contribute to the project by providing data, applications, technology and products to advance understanding the human brain.

Partners and collaborators

Beijing Normal University • Boston University • Fondazione Bruno Kessler • Harvard Medical School • Illinois Institute of Technology • Indiana University Bloomington • Indiana University School of Medicine • Indiana University-Purdue University Indianapolis • Indiana Unversity Bloomington • Italian Institute of Technology • Massachusetts Institute of Technology • National Institute of Information and Communication Technology • Northwestern University • Stanford University • The Jikei University School of Medicine • The Rockefeller University • The University of Washington • University Medical Center Groningen • University of Michigan • University of Oxford

Research areas and applications

Cognitive Neuroscience and Learning • Systems Neuroscience • Medical Sciences • Database for neuroimaging data management • Neuroinformatics • Neuroradiology • Biomedical Engineering • Scientific community tools • Information technology • Network neuroscience • Cognitive neuroscience of language • Statistics • Aging & social cognition research • Brain development • Psychological and brain sciences • Vision science and sports concussion research • Informatics and computing • Electrical engineering • Optometry • Computer science • Clinical neuroscience • Neuroimaging and radiology • Alzheimer disease and aging research • Rodent models • Computer Science • Computational neuroanatomy • Decision making and Neuroeconomics • Traumatic brain imaging • Visual brain development • Visual neuroscience and development • Ophthalmology • Systems neuroscience • Data Science • Big data and statistics • Clinical visual neurosciences

   The Brainlife platform is phenomenal. A great idea, great execution. It reminds me of Wikipedia when it started… now it is essential to almost everyone. - Tatiana Wolfe, The Ohio State University.

Brainlife Team

Franco Pestilli
Project Director
Lindsey Kitchell
Graduate Student
Brent McPherson
Graduate Student
Bradley Caron
Graduate Student
Dan Bullock
Graduate Student
Soichi Hayashi
Lead Developer
Steven O'Riley
Software Engineer
Kate Alpert
Software Engineer

Key collaborators

Robert Henschel

Director of Science Community Tools at Research Technologies, Indiana University

Eleftherios Garyfallidis

Assistant Professor of Intelligent Systems Engineering, Indiana University

Lei Wang

Assistant Professor of Psychiatry and Behavioral Sciences and Radiology, Northwestern University

Ivo Dinov

Associate Director for Education and Training, Michigan Institute for Data Science, University of Michigan