Data collected for A review on EEG-based music datasets

This narrative review has gathered and contrasted the distinct attributes of the openly accessible EEG datasets they are commonly used to develop (affective) Brain-computer Music related algorithms. We explored the strengths and drawbacks inherent in the attributes of the EEG datasets. Drawing from our investigation, we pinpointed 19 characteristics that make the music-based EEG datasets unique. We also briefly looked into how specific characteristics of the datasets that are openly accessible impact the performance and results of a study and influence the selection of machine learning techniques and preprocessing steps required to develop methods to build Brain-computer music interface algorithms. In conclusion, this study provides a guideline for choosing publicly available music-based EEG datasets for musicians and scientists working to develop reproducible, generalizable, and effective brain-computer music algorithms.