This repository contains the implementation of DECIFRA architecture designed for derivation of effective connectivity features from fMRI time series.

Codebase is being actively revised to make it more user-friendly and ready-to-use on new data.

1. Requirements

conda create -n dcfr python=3.12
conda activate dcfr
conda install pytorch torchvision torchaudio pytorch-cuda=11.3 -c pytorch -c nvidia
pip install -r requirements.txt

scripts/run_experiments.py options:

Required:

• mode:

  • tune - tune mode: run multiple experiments with different hyperparams
  • exp - experiment mode: run experiments with the best hyperparams found in the tune mode, or with default hyperparams default_HPs is set to True

• model: model for the experiment. Models' config files can be found at src/conf/model, and their sourse code is located at src/models

• dataset: dataset for the experiments. Datasets' config files can be found at src/conf/dataset, and their loading scripts are located at src/datasets.

Optional

• prefix: custom prefix for the project
  • default prefix is UTC time
  • appears in the name of logs directory
• HP_path: path to custom hyperparams to load
• follow_splits: path to an experiment with train/validation/test splits that you want to replicate in the new experiments.