1.2: Installing the Software and Downloading the Data

Installing Matlab

You will need Matlab version 2021a or later (2023b or later if you are using a Mac with Apple Silicon). Your Matlab installation must include the Signal Processing Toolbox. The Statistics and Machine Learning Toolbox is also required, but only for the decoding exercises in Chapter 12. Once you've installed Matlab, you can see what toolboxes are installed by typing ver on the Matlab command line. If you don't have the necessary toolboxes, contact your institution's IT support department for assistance.

Installing EEGLAB and ERPLAB

You will need EEGLAB 2025.1.0 or later and ERPLAB 13.1 or later to run all of the exercises in this book. New versions of Matlab, EEGLAB, and ERPLAB are released at least once per year, and these new versions can lead to changes in how things look (and occasionally changes in the results). To write this book, I mainly used Matlab 2024a, EEGLAB 2025.1.0, and ERPLAB 13.1 on a MacBook Pro running macOS 15.7. Everything should work fine if you use Windows or Linux, or if you use newer versions of EEGLAB or ERPLAB, but the screenshots will look a little different. You will almost certainly run into problems with older versions of Matlab, EEGLAB, and ERPLAB. See the Hardware and Software Requirements section for more details.

You must install EEGLAB before installing ERPLAB. You can find the documentation for EEGLAB, including instructions for downloading and installing, at https://eeglab.org. Make sure to install version 2025.1.0 or later. As noted in the EEGLAB installation instructions, you will need to update the Matlab PATH (whether you are installing EEGLAB for the first time or upgrading to a newer version). If you don’t know how to do this, or you can’t get EEGLAB to launch, you should read the description of how the PATH works in Section 1.6 of this chapter. If you're having trouble launching EEGLAB but the PATH isn’t the problem, see the ERPLAB FAQ page, the EEGLAB documentation, or the Troubleshooting Guide in Appendix 2. 

Once you’ve installed EEGLAB and updated the PATH, you should launch EEGLAB by typing eeglab in the Matlab command window. Screenshot 1.1 shows what it should look like when EEGLAB has been launched. Once you've verified that you can launch the EEGLAB GUI, you should quit it. Launching it once is important for getting some things set up, but you won't need the EEGLAB GUI for any of the exercises in this book (and you should not try to run it simultaneously with eStudio).

Once you have verified that EEGLAB is working, you can download and install ERPLAB (version 13.1 or later). The ERPLAB documentation, including installation instructions, can be found at https://github.com/lucklab/erplab/wiki. There are two ways to install ERPLAB. If you just want the latest major release, you can launch EEGLAB and use its built-in extensions manager by going to File > Manage EEGLAB extensions in the EEGLAB GUI. It will pop up a window with a list of extensions; select ERPLAB and click install/update. However, the EEGLAB extensions manager is sometimes out of date, and it might not contain the latest version of ERPLAB. To get the latest version (or an earlier version), you can manually download ERPLAB at https://github.com/ucdavis/erplab/releases. You can then follow the installation instructions at https://github.com/ucdavis/erplab/wiki/Installation. No matter which installation route you choose, make sure you download ERPLAB version 13.1 or later.

Once ERPLAB has been installed, you can launch it by typing estudio in the Matlab command window. It's a complex piece of software, so it takes some time to load, but you should see some progress information in the command window while it loads. Once it's done loading, you should see something like Screenshot 1.2. If it doesn't load, try running and then quitting EEGLAB again before launching eStudio.

Downloading Data for the Exercises

The datasets for the exercises are stored in a cloud storage system, and the master folder can be accessed at https://doi.org/10.18115/D5G045. This master folder contains a set of subfolders with the datasets for each chapter. Unfortunately, the cloud storage system may be blocked in some countries, but I have faith that clever readers will find a workaround that allows them to access the data. The data have been released with a Creative Commons license that permits them to be copied, used, remixed, and reposted as long as the original source is cited (see the license.txt file in each subfolder). Note that some of the folders are quite large and may take quite a while to download.