AI Use in EEG Data Processing

A survey for researchers who use, evaluate, or are considering artificial intelligence tools while processing and analyzing EEG data.

About this study

This survey explores how researchers in psychology, neuroscience, and cognitive science process and analyze EEG data, and how they use AI tools in that work.

This effort is co-led by Yu-Fang Yang, PhD (Freie Universität Berlin) and Arnaud Delorme, PhD (UC San Diego).

Data collection is now closed. Thank you to everyone who participated. The survey and the prize drawing are no longer accepting entries.

Everyone who entered the drawing will receive an email about the results by October 4, whether or not they won. There is no need to contact us before then. Questions can be sent to Yu-Fang Yang at yufang.yaang@gmail.com.

Survey responses are anonymized, stored without direct identifiers, and used in aggregate.

EEG processing refers to the steps that convert raw electroencephalographic recordings into analyzable signals and measures, including importing, montaging, filtering, bad-channel handling, re-referencing, artifact correction, epoching, baseline correction, time-frequency decomposition, source estimation, quality control, and statistical procedures.

Reviewed by the UC San Diego Office of IRB Administration and determined to be exempt, Protocol #815237.