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Foundation models for neuroscience tutorial

Tutorial repository for the Cajal school in machine learning for neuroscience.

Implements an NDT-1 style encoder from scratch (Ye and Pandarinath, 2021).

Running the tutorial in colab (recommended)

Open In Colab

Compiling the tutorial from the .py source

cd into the tutorials folder, and run:

jupytext tutorial_source.py --to ipynb -o Tutorial.ipynb

Working with the scripts

  • Fork this repository
  • Clone your fork
  • Create a fresh conda environment with e.g. Python 3.9, conda create --name fmn-tutorial python=3.11
  • cd into the directory and pip install -e .

There are three scripts available in the scripts folder:

  • preprocess_data.py: creates pickle files from DANDI sources
  • train_autoencoder.py: trains auto-encoders, similar to the tutorial, but on the command line, with better logging
  • predict_behavior.py: trains a decoder for behavior from scratch or from a pretrained checkpoint