brainhack week1

Neuro-Data Science Bootcamp at McGill


Week 1 will introduce participants to a computational reproducibility toolkit, as well as a basic grounding in supervised and unsupervised machine learning methods. Short lectures and hands-on tutorials throughout the five days will provide participants with familiarity applying these methods to real data. Dr Félix Antoine-Fortin (Calcul Québec) and Dr Manjari Narayan (Stanford University) will be residents during week 1. As a participant, at the end of Week 1 you should be able to answer questions such as:

  • What is version control, and how can I use it to improve my workflow?
  • Which data standards can be used to organize neuroimaging data, and why should I adopt them?
  • How should I visualize and define features for machine learning in neuroimaging?
  • What are the basic principles underlying deep learning, and how do they differ from classical machine learning?

A short quizz will be organized at the end of week 1, to check that participants have integrated the key points of the week. This quizz will count for 10% of the final note.

brainhack week2

Project definition at Université de Montréal

Week 2 will feature “pitch sessions”, where instructors give a short overview of skills or resources that can be incorporated into projects. Week 2 will be mostly focused on defining and piloting the project. As a participant, you will need to decide:

  • What general topic do you want to work on? e.g. group comparison using fMRI, software for analysis of MEG data
  • What skills do you want to learn, working on this project? e.g. preprocess fMRI data and run a classifier with sklearn, how to use git, etc.
  • What resources do you want to work on? e.g. the CORR dataset, the nipype library, the Glasser parcellation paper, etc.
  • What objectives do you want to achieve with the project? e.g. find differences in connectivity between two groups, replicate a multimodal brain parcellation, etc.
  • What will be the outcome(s) of your project? a short proceedings paper, a new public dataset, a new feature in a toolbox, etc.

Each project will go through one round of written submission and feedback, and revised by the end of week 2. This project description will count for 10% of the final note.

Université de Montréal CRIUGM

brainhack week3

Visualization and communication at Polytechnique Montréal


During week 3, participants will work on their project. Dr Joana Pereira (Karolinska Institute) will be resident for the week. The content of a typical day will include:

  • Work on projects. Most of the time will be reserved to actually doing the work.
  • Tutorials. Tutorials will be organized on demand.
  • Collaborate. There will be time each day for participants to help someone else with their project

By the end of week 3, participants will prepare a short video summarizing their project. This video will count for 10% of the final note.

brainhack week4

Project wrap up at Concordia

Week 4 will concentrate on finalizing project results and producing deliverables. Dr Pamela Douglas (University of California, Los Angeles), will be the resident for the week. Participants will have to produce a written deliverable for their project, such as a short BrainHack proceeding paper or a blog post. These deliverables will have to be submitted by September 6th (one week after the end of the school), and will count for 30% of the final grade. During week 4, participants will also make a short oral presentation of their project, which will count for 28% of the final grade. Finally, there will be a participation grade for the full 4 weeks, which will count for 12% of the final grade.