Search bioRxiv⌕ Search

Biology subjects

Jeung, S.

Publications and source records attributed to Jeung, S..

2 recordsLinked to original sources

Hexadirectional modulation of EEG gamma band activity

The medial temporal lobe (MTL) houses specialised cell types supporting spatial representation in the human brain. Among these are grid cells that encode the location of the navigator, displaying a geometrically structured anchoring to the environment. While macroscopic grid-cell-like coding in humans is typically investigated using functional magnetic resonance imaging or invasive electrophysiological methods in clinical populations, we demonstrate the feasibility of using non-invasive scalp electroencephalography (EEG) to capture the characteristic six-fold modulation of high-frequency activity source-localised to the MTL. We found hexadirectional modulations of the low- and high-gamma band activity by movement direction in virtual reality. Furthermore, individual preference to use an allocentric reference frame was linked to higher hexadirectional modulation in the low gamma band and encoding a location along the putative grid axes of high gamma band predicted faster retrieval of the remembered location. The use of scalp EEG to capture grid-cell-like activity and its functional relevance sets the foundation for investigating the MTL activity in richer experimental contexts.

neuroscience↗

The BeMoBIL Pipeline for automated analyses of multimodal mobile brain and body imaging data

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.

neuroscience↗