Deep learning

Team: Blake Richards, Jessica Thomson, Joseph Viviano, Yu Zhang

Date: November 15th, 2019, 9h-17h. Breakfast/registration at 8h30.

Summary: Deep learning is increasingly used in neuroscience research. This course is an introduction to deep learning geared towards neuroscientists, with the aim of gaining a basic understanding of:

  • principles of a deep neural network architecture.

  • convolutional neural networks.

  • variational auto-encoders.

  • graph convolutional neural networks.

In addition, a key objective of the course is to gain an understanding of how deep learning can be used for neuroscience research. Current approaches to link artificial and biological neural networks will thus be reviewed, and hands-on tutorials using neuro data will illustrate most of the presented notions.

Morning (9h-12h30): Foundation of deep learning

Afternoon (13h30-17h) intersection of deep learning and neuroscience


  • Basic familiarity with Python would be preferable

  • You will need enough space for Anaconda and all the course data.

Installation instructions

Please join the brainhack mattermost and the channel main-training-dl. To install training material locally, please download and install python with the full-suite 64-bit Anaconda distribution. Then download or clone the github repositories specific to each session: