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Applied Event-Related Potential Data Analysis (Luck)

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    If you place a metal disk (an electrode) on the skin overlying the skull, you can pick up voltages that are generated in the brain. This is the electroencephalogram or EEG. The EEG is a very complex signal that includes voltages associated with the thousands of different neural processes that are happening at any given moment in time. It's difficult to pull apart all of these different processes from the raw EEG, but a set of data processing operations can be applied to the EEG to pull out the electrical potentials (voltages) that are related to specific events, such as the appearance of a new object or an arm movement. These event-related potentials (ERPs) have proven to be very useful for studying a broad range of issues in the mind and brain sciences.

    The purpose of this book is to provide you with a practical overview of the data processing operations that are used to extract the ERPs from the EEG. This includes preprocessing operations that reduce noise and artifacts, the signal averaging operation at the core of extracting the ERPs, and the postprocessing operations that are used to convert the ERP waveforms into a small set of variables for statistical analysis. You will practice these operations using real data and an open-source Matlab ERP analysis package (ERPLAB Toolbox). You'll also learn how to automate the operations by writing simple Matlab scripts. Once you've gone through the exercises in this book, you should be ready to tackle the analysis of your own experiments.

    Cite as: Luck, S. J. (2022). Applied Event-Related Potential Data Analysis. LibreTexts. https://doi.org/10.18115/D5QG92

    This page titled Applied Event-Related Potential Data Analysis (Luck) is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by Steven J Luck directly on the LibreTexts platform.