This repository contains links and descriptions of all publicly shareable materials, code, data, etc. used by instructors at Neurohackademy 2019. The ordering of lectures and tutorials follows the chronology of the course.
-
Day 1 (07/29/2019)
- [09:00] Introduction to Neurohackademy (Ariel Rokem)
- [11:00] Reproducibility in fMRI: What is the problem? (Russ Poldrack)
- [13:00] The FAIR Data Principles (Mayann Martone)
- [14:00] Introduction to Docker (Anisha Keshavan)
- [14:00] Git and GitHub for collaboration (Elizabeth Dupre)
-
Day 2 (07/30/2019)
- [9:00] Plumbing the intertubes (Satra Ghosh) [repo]
- [10:00] Introduction to Python (Tal Yarkoni) [repo]
- [10:00] Building a Python library (Ariel Rokem)
- [13:00] Numerical computing in Python (JB Poline) [repo]
- [13:00] High-performance Python (Ariel Rokem)
- [15:00] Data visualization (Python) (Kirstie Whitaker) [repo]
- [15:00] Browser-based data visualization (Javascript) (Anisha Keshavan)
- [16:00] Model-based fMRI and HCP data (Noah Benson) [repo]
-
Day 3 (07/31/2019)
- [13:00] ML with Scikit Learn (Tal Yarkoni)
- [16:00] Jupyterlab and Binder (Elizabeth DuPre)
- [9:00] Measuring human functional brain networks (Caterina Gratton) [repo]
- [9:50] Functional brain parcellation (Pierre Bellec) [repo]
-
Day 4 (08/01/2019)
- [11:00] Meta-analysis and reproducibility (Angie Laird)
- [13:00] Optimization (Peng Zheng) [repo]
- [15:00] Cloud computing (Amanda Tan and Ariel Rokem)
- [9:00] (finding) Open datasets for neurohacking (Chris Gorgolewski)
-
Day 5 (08/02/2019)
- [11:00] Finding low-dimensional structure in large-scale neural recordings (Eva Dyer)
- [15:00] Optimal Transport (Zaid Harchaoui and Alec Greaves-Tunnell) [repo]
-
Day 6 (08/03/2019)