The HAPPE plus Event-Related (HAPPE+ER) Software: A Standardized Processing Pipeline for
Event-Related Potential Analyses

Event-Related Potential (ERP) designs are a common method for interrogating neurocognitive function in infancy with electroencephalography (EEG). However, the gold standard of preprocessing infant ERP data is manual-editing – a subjective, time-consuming processes. A number of automated pipelines have recently been created to address the need for standardization, automation, and quantification of EEG data processing; however, few are optimized for ERP analyses (especially in developmental or clinical populations). To fill this need, we propose and validate the HAPPE plus Event-Related (HAPPE+ER) software, a standardized and automated processing pipeline optimized for ERP analyses with infant data. HAPPE+ER processes event-related potential data from raw files through a series of filtering, line noise reduction, bad channel detection, artifact rejection from continuous data, segmentation, and bad segment rejection methods. HAPPE+ER also includes post-processing reports of both data quality and pipeline quality metrics to facilitate the evaluation and reporting of data processing in a standardized manner. Finally, HAPPE+ER includes a post-processing script to facilitate generating ERP figures and measures for statistical analysis. We compare multiple approaches with developmental visual evoked potential data to optimize and validate pipeline performance.

HAPPE+ER software is freely available under the terms of GNU General
Public License at https://github.com/PINE-Lab/HAPPE.

Alexa Monachino, Northeastern University, Boston, MA, United States