Machine Learning for the Cognitive Neurosciences
Online Workshop via Zoom
Registration: and use the 鈥淢L Academic registration鈥� 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 平特五不中 Centre for Integrative Neuroscience, HBHL鈥檚 NeuroHub and UNIQUE will hold a workshop entitled 鈥淢achine Learning for the Cognitive Neurosciences,鈥� 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 (平特五不中), 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, 平特五不中), 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 鈥� 12:00 Calcul Qu茅bec 鈥� 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 鈥� 12:00 Calcul Qu茅bec 鈥� Introduction to Programming with Python
Day 3 (Wednesday)
09:00 鈥� 10:30 Dr. Tal Yarkoni 鈥� 鈥淢achine Learning as Applied to Neuroimaging鈥�
10:30 鈥� 12:30 Alexandre Hutton 鈥� Hands-on ML: dataset handling, sklearn/nilearn, estimators & models, model evaluation
13:30 鈥� 16:00 Practical exercises
Day 4 (Thursday)
09:00 鈥� 12:30 Alexandre Hutton 鈥� Hands-on ML: cross-validation, ROC & AUC, visualization, evaluation metrics
13:30 鈥� 16:00 Practical exercises
Day 5 (Friday)
09:00 鈥� 10:00 Dr. Ella Gabitov 鈥� 鈥淭he elephant in the room: to explain or to predict, that is the question鈥�
10:00 鈥� 12:30 Alexandre Hutton 鈥� Hands-on ML: confounds. model interpretation (and lack thereof)
13:30 鈥� 16:30 Practical exercises, data clinic
