The HAPPE plus Event-Related (HAPPE+ER) software: A standardized preprocessing pipeline for event-related potential...

Area of Science:

• Neuroscience
• Cognitive Science
• Biomedical Engineering

Background:

• Electroencephalography (EEG) is crucial for studying neurocognitive function using Event-Related Potential (ERP) designs.
• Traditional manual preprocessing of ERP data is subjective and time-consuming.
• Existing automated EEG preprocessing pipelines often lack optimization for ERP analyses, particularly in diverse populations.

Purpose of the Study:

• To introduce and validate HAPPE+ER, a novel automated preprocessing pipeline for ERP analysis.
• To provide a standardized, efficient, and quantifiable method for ERP data processing across the lifespan.
• To enhance data quality assessment and facilitate pipeline performance evaluation.

Main Methods:

• Development and validation of the HAPPE+ER software pipeline.
• Processing of event-related potential data from raw files to statistical analysis-ready outputs.
• Inclusion of post-processing reports for data and pipeline quality metrics.
• Implementation of scripts for validating HAPPE+ER performance using simulated and real ERP data.

Main Results:

• HAPPE+ER offers a standardized and automated approach to ERP preprocessing.
• The pipeline is optimized for ERP analyses, including developmental and clinical populations.
• Post-processing reports provide objective measures of data and pipeline quality.
• Validation methods allow for performance comparison with other preprocessing techniques.

Conclusions:

• HAPPE+ER provides a robust, automated solution for ERP data preprocessing.
• The software enhances standardization, efficiency, and quantifiability in EEG research.
• HAPPE+ER is a valuable tool for researchers across various lifespan populations, facilitating reproducible and reliable neurocognitive studies.