Machine Learning for the Cognitive Neurosciences
Online Workshop via Zoom
Registration: and use the “ML Academic registration” ticket when prompted (Registering for the Calcul Quebec Python event automatically registers you for the entire workshop).
From the 18th to 22nd of January, 2021, the lab, the McGill Centre for Integrative Neuroscience, HBHL’s NeuroHub and UNIQUE will hold a workshop entitled “Machine Learning for the Cognitive Neurosciences,” whose objective will be to introduce researchers to both the conceptual and practical rudiments of machine learning as applied to neuroimaging. See preliminary schedule below.
Though attendees are expected to have a general familiarity with brain imaging and conventional statistical analyses, the first two days introduce attendees to the software environment that will serve for the practical exercises during the workshop, including some basics of the Linux command line (Bash), Git, the Python programming language, and several Python-based packages for scientific computing, courtesy of .
The core content will be presented over the remaining days. The first speaker, Dr. Tal Yarkoni (University of Texas at Austin) will discuss the scientific applications of machine learning in brain imaging. The second speaker, Dr. Ella Gabitov (Ď㽶ĘÓƵ), will present on the explanatory power and limitations of machine learning when applied to cognitive neuroscience. Throughout the workshop, hands-on tutorials will be presented by Alexandre Hutton (ORIGAMI, McGill), which will focus on giving participants an understanding of core concepts and common practices in machine learning.
Preliminary Schedule
Day 1 (Monday)
Group 1:
09:00 – 12:00 Calcul Québec – Introduction to Programming with Python
Group 2:
09:00 - 10:00 Linux command line: Bash.
10:00 - 11:00 ORIGAMI - Git & version control
Day 2 (Tuesday)
Group 1:
09:00 - 10:00 Linux command line: Bash.
10:00 - 11:00 ORIGAMI - Git & version control
Group 2:
09:00 – 12:00 Calcul Québec – Introduction to Programming with Python
Day 3 (Wednesday)
09:00 – 10:30 Dr. Tal Yarkoni – “Machine Learning as Applied to Neuroimaging”
10:30 – 12:30 Alexandre Hutton – Hands-on ML: dataset handling, sklearn/nilearn, estimators & models, model evaluation
13:30 – 16:00 Practical exercises
Day 4 (Thursday)
09:00 – 12:30 Alexandre Hutton – Hands-on ML: cross-validation, ROC & AUC, visualization, evaluation metrics
13:30 – 16:00 Practical exercises
Day 5 (Friday)
09:00 – 10:00 Dr. Ella Gabitov – “The elephant in the room: to explain or to predict, that is the question”
10:00 – 12:30 Alexandre Hutton – Hands-on ML: confounds. model interpretation (and lack thereof)
13:30 – 16:30 Practical exercises, data clinic
