The Maryland analysis of developmental EEG (MADE) pipeline

Compared to adult EEG, EEG signals recorded from pediatric populations have shorter recording periods and contain more artifact contamination. Therefore, pediatric EEG data necessitate specific preprocessing approaches in order to remove environmental noise and physiological artifacts without losing...

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Bibliographic Details
Published in:Psychophysiology Vol. 57; no. 6; pp. e13580 - n/a
Main Authors: Debnath, Ranjan, Buzzell, George A., Morales, Santiago, Bowers, Maureen E., Leach, Stephanie C., Fox, Nathan A.
Format: Journal Article
Language:English
Published: United States Blackwell Publishing Ltd 01.06.2020
Subjects:
Adolescent
automated
Automation
Child
Child, Preschool
Contamination
Datasets as Topic
EEG
Electroencephalography
Electroencephalography - methods
Electroencephalography - standards
Functional Neuroimaging - methods
Functional Neuroimaging - standards
Humans
Infant
pediatric
Pediatrics
pipeline
Pipelines
preprocessing
Reproducibility of Results
Signal Processing, Computer-Assisted
Standardization
United States > US
Maryland
pipeline
automated
preprocessing
EEG
pediatric
ISSN:0048-5772, 1469-8986, 1469-8986, 1540-5958
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Description
Summary:Compared to adult EEG, EEG signals recorded from pediatric populations have shorter recording periods and contain more artifact contamination. Therefore, pediatric EEG data necessitate specific preprocessing approaches in order to remove environmental noise and physiological artifacts without losing large amounts of data. However, there is presently a scarcity of standard automated preprocessing pipelines suitable for pediatric EEG. In an effort to achieve greater standardization of EEG preprocessing, and in particular, for the analysis of pediatric data, we developed the Maryland analysis of developmental EEG (MADE) pipeline as an automated preprocessing pipeline compatible with EEG data recorded with different hardware systems, different populations, levels of artifact contamination, and length of recordings. MADE uses EEGLAB and functions from some EEGLAB plugins and includes additional customized features particularly useful for EEG data collected from pediatric populations. MADE processes event‐related and resting state EEG from raw data files through a series of preprocessing steps and outputs processed clean data ready to be analyzed in time, frequency, or time‐frequency domain. MADE provides a report file at the end of the preprocessing that describes a variety of features of the processed data to facilitate the assessment of the quality of processed data. In this article, we discuss some practical issues, which are specifically relevant to pediatric EEG preprocessing. We also provide custom‐written scripts to address these practical issues. MADE is freely available under the terms of the GNU General Public License at https://github.com/ChildDevLab/MADE-EEG-preprocessing-pipeline. This article presents the Maryland Analysis of Developmental EEG (MADE) pipeline, an automated preprocessing pipeline for EEG data that can be used with EEG recorded with different systems, populations, levels of artifact contamination, and lengths of recording. MADE is based on MATLAB and includes customized features particularly useful for EEG data collected from pediatric populations.
Bibliography:Funding information
This work was supported by the National Institute of Health (1UG3OD023279‐01, P01HD064653, U01MH093349).
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ISSN:0048-5772
1469-8986
1469-8986
1540-5958
DOI:10.1111/psyp.13580