PT  - JOURNAL ARTICLE
AU  - M. Klug
AU  - S. Jeung
AU  - A. Wunderlich
AU  - L. Gehrke
AU  - J. Protzak
AU  - Z. Djebbara
AU  - A. Argubi-Wollesen
AU  - B. Wollesen
AU  - K. Gramann
TI  - The BeMoBIL Pipeline for automated analyses of multimodal mobile brain and body imaging data
AID  - 10.1101/2022.09.29.510051
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.09.29.510051
4099  - http://biorxiv.org/content/early/2022/10/06/2022.09.29.510051.short
4100  - http://biorxiv.org/content/early/2022/10/06/2022.09.29.510051.full
AB  - Advancements in hardware technology and analysis methods allow more and more mobility in electroencephalography (EEG) experiments. Mobile Brain/Body Imaging (MoBI) studies may record various types of data such as motion or eye tracking in addition to neural activity. Although there are options available to analyze EEG data in a standardized way, they do not fully cover complex multimodal data from mobile experiments. We thus propose the BeMoBIL Pipeline, an easy-to-use pipeline in MATLAB that supports the time-synchronized handling of multimodal data. It is based on EEGLAB and fieldtrip and consists of automated functions for EEG preprocessing and subsequent source separation. It also provides functions for motion data processing and extraction of event markers from different data modalities, including the extraction of eye-movement and gait-related events from EEG using independent component analysis. The pipeline introduces a new robust method for region-of-interest-based group-level clustering of independent EEG components. Finally, the BeMoBIL Pipeline provides analytical visualizations at various processing steps, keeping the analysis transparent and allowing for quality checks of the resulting outcomes. All parameters and steps are documented within the data structure and can be fully replicated using the same scripts. This pipeline makes the processing and analysis of (mobile) EEG and body data more reliable and independent of the prior experience of the individual researchers, thus facilitating the use of EEG in general and MoBI in particular. It is an open-source project available for download at https://github.com/BeMoBIL/bemobil-pipeline which allows for community-driven adaptations in the future.Competing Interest StatementThe authors have declared no competing interest.