DISCLAIMER: This version of HAPPE is outdated! For the newest version, click the button below.

Harvard Automated Processing Pipeline for EEG (HAPPE 1.0)

HAPPE 1.0 is suitable for:

  • task-free EEG data (aka resting-state or baseline EEG)

  • task-related EEG data (for time-frequency analyses)

  • EEG with 20+ electrodes

  • EEG systems that have 10-20 system channels or spatial equivalents

Don’t see your analysis of interest or EEG system in the list above? Check our other software pages which expand the original HAPPE functionality and compatibility with different EEG configurations.

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Implementing HAPPE 1.0

There are two ways to implement HAPPE 1.0 software: (A) through our stand-alone HAPPE 1.0 scripts, or (B) through our BEAPP software. HAPPE 1.0 implemented through BEAPP offers additional batch-processing options, feature calculation after pre-processing, and settings to facilitate data processing in multi-site or large-scale longitudinal settings.

A. Implementing HAPPE through stand-alone HAPPE 1.0 software:

To facilitate implementation of HAPPE 1.0, we include an example dataset of EEG files with visualizations at each step of HAPPE 1.0 processing in our supplemental materials in the Gabard-Durnam et al., 2018 manuscript.

After downloading the HAPPE 1.0 folder from GitHub, we recommend:

  1. Reading the README file for HAPPE

  2. Downloading and processing the example dataset, checking your outputs with the visualizations we provide in the manuscript.

  3. Running several of your files in the “visualization” mode to examine how default HAPPE settings perform with your data.

  4. When you are satisfied with your HAPPE user-specified options, you may run your data in batch mode (recommended for speed) by turning off the visualization setting.

B. Implementing HAPPE 1.0 through BEAPP software:

You may also implement HAPPE 1.0 in our Batch EEG Automated Processing Platform (BEAPP) software (see figure at right for options in BEAPP). HAPPE 1.0 in BEAPP seamlessly integrates contemporary pre-processing with analysis approaches. BEAPP also contains a GUI if you prefer that interface. To learn more about BEAPP, please see our paper on this software by Levin et al., 2018.

Please note that BEAPP continues to evolve, so check the latest version of the software for up-to-date capabilities and supported EEG systems.

To implement HAPPE 1.0 in BEAPP, we recommend the same steps as when implementing HAPPE 1.0 stand-alone software, with the additional step of FIRST reading the BEAPP README file and manuscript.

Get BEAPP