Alice dataset for Eelbrain

This repository contains scripts and instructions to reproduce the results from the paper Eelbrain: A toolkit for continuous analysis with temporal response functions.

Setup

Download this repository

If you're familiar with git, clone this repository. If not, simply download it as a zip file.

Create the Python environment

The easiest way to install all the required libraries is with conda, which comes with the Anaconda Python distribution. Once conda is installed, simply run, from the directory in which this README file is located:

$ conda env create --file=environment.yml

This will install all the required libraries into a new environment called eelbrain. Activate the new environment with:

$ conda activate eelbrain

Download the Alice dataset

Download the Alice EEG dataset. This repository comes with a script that can automatically download the required data from UMD DRUM by running:

$ python download_alice.py

The default download location is ~/Data/Alice. The scripts in the Alice repository expect to find the dataset at this location. If you want to store the dataset at a different location, provide the location as argument for the download:

$ python download_alice.py download/path

then either create a link to the dataset at ~/Data/Alice, or change the root path where it occurs in scripts (always near the beginning).

This data has been derived from the original dataset using the script at import_dataset/convert-all.py.

Notebooks

Many Python scripts in this repository are actually Jupyter notebooks. They can be recognized as such because of their header that starts with:

# ---
# jupyter:
#   jupytext:
#     formats: ipynb,py:light

These scripts were converted to Python scripts with Jupytext for efficient management with git. To turn such a script called notebook.py back into a notebook, run:

$ jupytext --to notebook notebook.py

Subdirectories

Predictors

The predictors directory contains scripts for generating predictor variables. These should be created first, as they are used in many of the other scripts:

make_gammatone.py: Generate high resolution gammatone spectrograms which are used by make_gammatone_predictors.py
make_gammatone_predictors.py: Generate continuous acoustic predictor variables
make_word_predictors.py: Generate word-level predictor variables consisting of impulses at word onsets

Analysis

The analysis directory contains scripts used to estimate and save various mTRF models for the EEG dataset. These mTRF models are used in some of the figure scripts.

Figures

The figures directory contains the code used to generate all the figures in the paper.

Further resources

This tutorial and dataset:

Eelbrain:

Other libraries:

hans/Alice