The EEG Cookbook: A Practical Guide to Neuroergonomics Research

Nathan Sanders, Sanghyun Choo, Chang S. Nam

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

Abstract

Conducting an EEG-based neuroergonomics experiment can be a daunting task for novice researchers. This chapter provides an overview of three aspects of EEG research which we hope will help novice researchers efficiently produce meaningful and replicable results: power analysis, data preprocessing, and reporting. We explain why power analysis and sample size estimation are critical yet often overlooked aspects of experimental research and describe the most common measures of effect size likely to be encountered, Cohen’s d and eta-squared. We also provide a list of powerful (and free) power analysis tools to facilitate the actual calculations. We also provide step-by-step instructions for data preprocessing with EEGLAB which can be used in preparation for subsequent ERP or connectivity analyses. This includes filtering, artifact removal and correction, independent component analysis, and source localization. Finally, we condense EEG reporting guidelines into a checklist which can be used to ensure that your manuscript draft follows best practices.

Original languageEnglish
Title of host publicationCognitive Science and Technology
PublisherSpringer
Pages33-51
Number of pages19
DOIs
StatePublished - 2020
Externally publishedYes

Publication series

NameCognitive Science and Technology
ISSN (Print)2195-3988
ISSN (Electronic)2195-3996

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