Neurohackademy 2018 course materials

This repository contains links and descriptions of all publicly shareable materials, code, data, etc. used by instructors at Neurohackademy 2018. The ordering of lectures and tutorials follows the chronology of the course.

• Day 1 (07/30/2018)

  • [09:00] Introduction to Neurohackademy (Ariel Rokem)
  • [10:30] Reproducibility in fMRI: What is the problem? (Russ Poldrack)
  • [13:00] Git/Github (Bernease Herman)
  • [13:00] Docker for Scientists (Chris Gorgolewski) [repo]
  • [14:30] Introduction to R (Valentina Staneva)
  • [14:30] Introduction to Python (Tal Yarkoni) [repo] [video]
  • [16:00] Software Testing for Scientists (Chris Gorgolewski) [repo]
  • [17:00] Science: Open for All (Kirstie Whitaker)

• Day 2 (07/31/2018)

  • [09:00] From interactive exploration to reproducible data science: Jupyter, Binder, Travis and friends (Fernando Perez) [repo] [video]
  • [13:00] Numerical computing for neuroimaging (JB Poline) [repo]
  • [13:00] Python Packaging (Ariel Rokem)
  • [14:30] Visualization in Python: An overview (Tal Yarkoni) [repo]
  • [14:30] Image processing and computer vision with scikit-image (Michael Beyeler) [video]
  • [15:30] Data manipulation in pandas (Tal Yarkoni) [repo] [video]
  • [15:30] High Performance Python (Ariel Rokem) [repo]
  • [17:00] Deep Learning with keras (Ariel Rokem) [repo] [video]

• Day 3 (08/01/2018)

  • [10:30] Ethical Issues in Neural Data Collection and Use (Eran Klein) [video]
  • [13:00] Machine learning with scikit-learn (Jake Vanderplas) [repo] [video]
  • [16:00] The Brain Imaging Data Structure (BIDS) (Chris Gorgolewski) [video]
  • [17:00] BIDS: Tools and Services (Chris Gorgolewski)
  • [17:00] Introduction to web technologies (Anisha Keshavan) [video]

• Day 4 (08/02/2018)

  • [09:00] Cloud computing with AWS (Amanda Tan and Ariel Rokem) [repo] [video]
  • [13:00] Panel Discussion: Fostering Open Science Communities (Chris Gorgolewski, Fernando Perez, Kirstie Whitaker, Gael Varoquaux, Satra Ghosh) [video]
  • [14:45] Software pipelines for reproducible neuroimaging (Chris Gorgolewski and Satra Ghosh) [repo] [video]

• Day 5 (08/03/2018)

  • [09:00] Predictive models using object-oriented, interactive analysis in Matlab: Tools and application to pain (Tor Wager) [repo] [video]
  • [13:00] Finding low-dimensional structure in large-scale neural recordings (Eva Dyer) [video]
  • [15:00] AllenSDK and the Allen Brain Observatory (Nicolas Cain and Justin Kiggins) [video]
  • [17:00] P-values and Reproducibility Issues (JB Poline) [video]

• Day 6 (08/06/2018)

  • [09:00] Machine Learning in Neuroimaging (Gael Varoquaux) [video]
  • [13:00] R for statistical analysis of fMRI data (Tara Madhyastha) [video]
  • [15:00] Synthesizing fMRI using generative adversarial networks: cognitive neuroscience applications, promises and pitfalls (Sanmi Koyejo) [video]
  • [17:00] Introduction to Brainhacking (Cameron Craddock) [video]