DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience

Abstract

ABSTRACTBiomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher- dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets, the LEMON dataset, containing 213 EEG recordings of healthy participants, and the TDBRAIN dataset, containing 1274 EEG recordings, mainly from patients with a psychiatric condition. Additionally, we performed an exploratory analysis of the LEMON dataset that could inspire biomarkers of healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function.