Brainhack is transformative.


Eat, code, eat, code, sleep.


Meet your old friend or make new ones.

"Join us on the Brainhack Mattermost to connect with the community and start planning your project! Our channel name is #brainhack-mtl."

First-day presentation

Learn! Hack! Discuss! Share!

In full brainhack spirit, there will be:


Tutorials, resources, and hands-on sessions for neuroimaging tools and methods. From how-to-code (python! julia! version control!) to how-to-plot: we got you covered!


Lots of free hacking time to tinker with a project of your choice. You can browse already submitted projects and get ready to pitch your own during our first day


Short sessions to present your research or discuss topics of interest in an informal setting. We’re planning on having debates on the future of scientific journals & conferences: bring your best questions and suggestions!


Meet or check-in with experts and peers, share ideas, and plant the seeds of future collaborations. There’s gonna be a gathertown space full of games and a trivia night! We’ll miss the physical high-fives, but we’ll be there for you!

Tutors & Instructors

we are going to listen to, learn from, and chat with:

Testimonial author

Yann Harel

CoCoLab, Université de Montréal

An overview of MNE-Python, including a hands-on on common use cases and recommendations for designing a M/EEG analysis pipeline, from raw data to power and connectivity measures.

Testimonial author

Dorota Jarecka

Massachusetts Institute of Technology

Introduction to Pydra - a new workflow engine for Nipype 2.0

Testimonial author

Danilo Bzdok

Dpt. of Biomedical Engineering, Faculty of Medicine, McGill University / Mila - Quebec AI Institute

Machine-learning workflows for high-dimensional neuromaging datasets

Testimonial author

Ella Gabitov

McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University

Questioning our questions and models in neuroimaging

Testimonial author

Guillaume Dumas

CHU Sainte-Justine / Dpt. of Psychiatry, Université de Montréal / Mila - Quebec AI Institute

Introduction to Python & to Julia and Experimenting with reproducibility in bio/neuro-informatics

Testimonial author

Kendra Oudyk

McGill University

Git & Github Tutorial + Q&A

Testimonial author

Anibal Solon

Computational Neuroimaging Lab, The University of Texas at Austin

Git & Github Tutorial + Q&A

Testimonial author

Sebastian Urchs

Montreal Neurological Institute, Origami Lab / Douglas Research Centre, CoBra Lab

Let the visualization do the work: how interactive visualization can make your life easier and your figures pretty to look at.

Testimonial author

Loic Tetrel


Hands on Neurolibre, a cloud-based and curated repository for jupyter notebooks in neuroscience.

Testimonial author

Jean-Baptiste Poline

Montreal Neurological Institute, McGill University/ NeuroHub

Questioning our questions and models in neuroimaging

Testimonial author

Patrick Mineault


Test-driven development


Find our schedule on Google Calendar here!

Brought to you by

Valentina Borghesani
Samuel Guay
Désirée Lussier
And all the Brainhack Team!

Friends & sponsors

We acknowlege the generous support of


Feel free to join any project you are interested in!

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Make Brainhack Accessible WorldWide: Translation of Brainhack Glossary into Different Languages

The project aims to bring together Brainhack and Open Science terminologies together in one glossary to help to the new comers to guide them through …

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Neuroimaging Cookbook 🧠🍳📓

Anyone ever Google how to accomplish a task for neuroimaging data more than once? For example, I’ve Googled “how to extract a mask from a …

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OpenMentalizing: leveraging open neurological data for uncovering the differences in mentalizing/empathy capabilities

Mentalizing is a higher cognitive ability that is vital for the social life of an individual. New brain imaging techniques have investigated neural …

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Pydesperate times call for Pydrastic measures

Nipype is a Python library that provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages …

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Standardized denoising strategies with fMRIprep

abels There are many strategies that have been proposed in the literature to denoise fMRI time series, and fMRIprep implements many of them. However, …

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Contact Us

Whether you have questions or you would just like to say hello, feel free to reach out.

Brainhack Global main website


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