The Batch Electroencephalography Automated Processing Platform (BEAPP)

<p>The Boston EEG Automated Processing Pipeline (BEAPP) is a modular, Matlab-based software designed to facilitate automated, flexible batch processing of baseline and event-related EEG files in datasets with mixed acquisition formats.</p> <p>Rather than prescribing a specified set of EEG processing steps, BEAPP allows users to choose from a menu of options. Each option can be turned on or off, and options turned &ldquo;on&rdquo; can be tailored to fit the user&rsquo;s needs.&nbsp; BEAPP currently provides options for the following user-controlled modules:</p> <ol> <li><a href="http://journal.frontiersin.org/article/10.3389/fninf.2015.00016/full">PREP Pipeline</a></li> <ol> <li>Line noise removal, interpolation of bad channels, robust average referencing</li> </ol> <li>Filtering</li> <ol> <li>High-pass</li> <li>Low-pass</li> <li>Notch</li> <li><a href="http://www.nitrc.org/projects/cleanline">CleanLine</a></li> </ol> <li>Resampling</li> <li>Independent Components Analysis (ICA) with optional use of&nbsp;<a href="https://github.com/irenne/MARA">MARA</a>&nbsp;artifact classifier</li> <li><a href="https://www.frontiersin.org/articles/10.3389/fnins.2018.00097/full">HAPPE Pipeline</a> (<b>Note:</b> see <a href="https://www.frontiersin.org/articles/10.3389/fnins.2018.00513/full#supplementary-material">supplementary material</a> for appropriate modules and inputs to toggle when running HAPPE)</li> <ol> <li>Select 10-20 channel locations, and other channels of interest</li> <li>1 Hz high-pass filter</li> <li>CleanLine to remove line noise</li> <li>Wavelet cleaning</li> <li>ICA with MARA</li> <li>Interpolate bad channels</li> <li>Average reference</li> </ol> <li>Re-Referencing</li> <ol> <li>Laplacian (<a href="http://psychophysiology.cpmc.columbia.edu/Software/CSDtoolbox/">CSDLP</a>)</li> <li>Average re-referencing</li> <li>Reference to individual or subset of electrodes</li> <li><a href="https://www.frontiersin.org/articles/10.3389/fnins.2017.00601/full">REST</a></li> </ol> <li>Detrending</li> <ol> <li>Mean</li> <li>Linear</li> <li>Kalman</li> </ol> <li>Amplitude-based artifact detection for segment removal</li> <li>Segmentation</li> <ol> <li>Stimulus-locked (for task-related data)</li> <li>Non-stimulus-locked (for continuous or &ldquo;resting&rdquo; data)</li> </ol> <li>Power spectral decomposition (PSD)</li> <li>Inter-trial phase coherence (ITPC)</li> </ol> <p>BEAPP aims to strike a balance between assuming only a basic level of MATLAB and EEG signal processing experience, while also offering a flexible menu of opportunities for more advanced users.&nbsp; At a minimum, no programming experience is required to use BEAPP, but basic familiarity with troubleshooting in Matlab will likely come in handy.</p> <p>User guides for running BEAPP programmatically and using a GUI can be found in the documentation folder.</p> <p><strong>Next Steps:</strong></p> <p>BEAPP is intended to be a dynamic, rather than static, platform for EEG processing.&nbsp; This means that we plan to continue adding additional functionality over time, and we encourage other users to add functionality as well.&nbsp;</p> <p><strong>What&rsquo;s on Our Wishlist (coming soon):</strong></p> <ol> <li>Improved GUI for user inputs</li> <li>Formatted dataset-wide run reporting (general dataset statistics, formatted warnings in a report)</li> <li>Reading files in directly from .bdf/.edf and .set files</li> <li>Coherence</li> <li>Phase lag index</li> <li>Topoplotting outputs with mixed source acquisition layouts/ number of channels</li> <li>Phase amplitude coupling</li> <li>Ability to change the order of modules</li> </ol> <p>&nbsp; In publications, please reference:

Levin AR, Méndez Leal AS, Gabard-Durnam LJ, and O'Leary, HM. <a href="https://www.frontiersin.org/articles/10.3389/fnins.2018.00513/full"> BEAPP: The Batch Electroencephalography Automated Processing Platform</a>. Frontiers in Neuroscience (2018).

<p>Correspondence: April R. Levin, MD&nbsp;<a href="mailto:april.levin@childrens.harvard.edu">april.levin@childrens.harvard.edu</a></p> <p><strong>Additional Credits: </strong></p> <p>BEAPP utilizes functionality from the software listed below. Users who choose to run any of this software through BEAPP should cite the appropriate papers in any publications.</p> <p><a href="http://sccn.ucsd.edu/wiki/EEGLAB_revision_history_version_14">EEGLAB Version 14.1.2b</a>:</p> <p>Delorme A &amp; Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics. Journal of Neuroscience Methods 134:9-21</p> <p><a href="https://github.com/VisLab/EEG-Clean-Tools">PREP pipeline Version 0.52:&nbsp;</a></p> <p>Bigdely-Shamlo N, Mullen T, Kothe C, Su K-M and Robbins KA (2015) The PREP pipeline: standardized preprocessing for large-scale EEG analysis Front. Neuroinform. 9:16. doi: 10.3389/fninf.2015.00016</p> <p><a href="http://psychophysiology.cpmc.columbia.edu/Software/CSDtoolbox/">CSD Toolbox:&nbsp;</a></p> <p>Kayser, J., Tenke, C.E. (2006). Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: I. Evaluation with auditory oddball tasks. Clinical Neurophysiology, 117(2), 348-368</p> <p>Users using low-resolution (less than 64 channel) montages with the CSD toolbox should also cite: Kayser, J., Tenke, C.E. (2006). Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: II. Adequacy of low-density estimates. Clinical Neurophysiology, 117(2), 369-380</p> <p><a href="https://www.frontiersin.org/articles/10.3389/fnins.2018.00097/full">HAPPE</a>:</p> <p>Gabard-Durnam, L. J., Mendez Leal, A. S., Wilkinson, C. L., &amp; Levin, A. R. (2018). The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): standardized processing software for developmental and high-artifact data. Frontiers in Neuroscience (2018).</p> <p><a href="https://www.frontiersin.org/articles/10.3389/fnins.2017.00601/full">The REST Toolbox</a>:</p> <p>&nbsp;Li Dong*, Fali Li, Qiang Liu, Xin Wen, Yongxiu Lai, Peng Xu and Dezhong Yao*. MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG. Frontiers in Neuroscience, 2017:11(601).</p> <p><a href="https://irenne.github.io/artifacts/">MARA</a>:</p> <p>Winkler et al., Automatic Classification of Artifactual ICA-Components for Artifact Removal in EEG Signals. Behavioral and Brain Functions 7:30 (2011).</p> <p><a href="http://www.nitrc.org/projects/cleanline">CleanLine</a>:</p> <p>Mullen, T. (2012).&nbsp;<em>NITRC: CleanLine: Tool/Resource Info</em>.</p> <p><strong>Requirements:</strong></p> <p>&nbsp;BEAPP was written in Matlab 2016a. Older versions of Matlab may not support certain functions used in BEAPP.</p> <p>&nbsp;</p>