ABSTRACT
Biomarker 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 mostly subjective. 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 standard EEG-BIDS structure 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 exemplify the use of the pipeline for biomarker discovery in healthy ageing in the LEMON dataset, containing 212 healthy participants. We demonstrate its utility to speed up biomarker discovery in a clinical setting with a new dataset containing 74 patients with chronic pain. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse and analysis of large EEG datasets, promoting open and reproducible research on brain function.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
