Alice dataset for Eelbrain

This repository contains scripts and instructions to reproduce the results from Eelbrain, a toolkit for time-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 using the environment file provided in this repository (environment.yml) as described in the Instructions for installing Eelbrain: Full Setup.

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/directory

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.

Create (or download) predictors and TRFs

In order to create predictors used in the analysis (and for some plots in the figures), execute the scripts in the predictors directory (see Subdirectories below).

All TRFs used in the different figures can be computed and saved using the scripts in the analysis directory. However, this may require substantial computing time. To get started faster, the TRFs can also be downloaded from the data repository (TRFs.zip). Just move the downloaded TRFs folder into the ~/Data/Alice directory, i.e., as ~/Data/Alice/TRFs.

Note

Replicability: Due to numerical issues, results can differ slightly between different operating systems and hardware used. Similarly, implementation changes (e.g., optimization) can affect results, even if the underlying algorithms are mathematically equivalent. Changes in the boosting implementation are noted in the Eelbrain Version History.

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 back into a notebook, run this command (assuming the script is called my_trf_analysis.py):

$ jupytext --to notebook my_trf_analysis.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.

Import_dataset

This directory contains the scripts that were used to convert the data from the original Alice EEG dataset to the format used here.

Experimental pipeline

The pipeline directory contains instructions for using an experimental pipeline that simplifies and streamlines TRF analysis. For more information, see the Pipeline Readme file.

Further resources

This tutorial and dataset:

• Ask questions
• Report issues

Eelbrain:

• Command reference
• Examples
• Ask questions
• Report issues

Other libraries:

• Matplotlib
• MNE-Python