2025-10-02 –, Jean-Baptiste Say Amphitheater
Language: English
In this 10-minute talk, we will explore how UnfoldMakie.jl visualizes electrical activity of the brain recorded from the scalp. It works with electroencephalographic (EEG) data and such techniques as event-related potentials (ERPs) and regression-based ERPs (rERPs). UnfoldMakie integrates ERP and rERP analysis from Unfold.jl with interactive, customizable plotting from Makie.jl. This session will demonstrate how to create interactive and insightful visualizations of scalp electrical activity in Julia.
UnfoldMakie.jl is a Julia package designed to simplify the visualization of EEG data, ERP and regression ERP (rERP), focusing on flexibility, speed, and interactivity (Mikheev & Ehinger, 2025). UnfoldMakie combines the powerful techniques for ERP and rERP analysis from Unfold.jl with the high-performance plotting capabilities of Makie.jl and the flexible, declarative plotting approach of AlgebraOfGraphics.jl. This integration provides an intuitive interface for creating detailed, customizable plots that help researchers interpret and present their data more effectively.
This work builds on the research presented in Mikheev et al. (2024), where we conducted a user study to analyze the usage of existing EEG tools, gathering feedback on user preferences, challenges, and needs. The insights from this study informed the design of UnfoldMakie.jl, ensuring it addresses real-world user demands and overcomes common difficulties faced with other EEG software tools.
In this session, we'll walk through the core features and functionality of UnfoldMakie, including:
• Getting Started: Setting up UnfoldMakie and importing data. Glossary of ERP plot types and how they were implemented in the package. Comparison with other non-Julia tools.
• Visualizing Data: Creating interactive ERP and EEG plots for the most of existing ERP plot types, from simple time-series graphs to complex topographic plots.
• Regression ERP (rERP) Analysis: Introducing rERP and demonstrating how UnfoldMakie can handle regression-based ERP analysis, making it easier to visualize the effects of predictors on event-related potentials.
• Customization: Customizing plots to fit specific research needs, with options for multi-plot layouts, dynamic data adjustments, and visual tweaks.
• Future Directions: Discussing the roadmap for UnfoldMakie, including planned features for more flexible visualization options, and the addition of various uncertainty visualization techniques.
This talk will cater to those working in Julia with time-series data in fields such as neuroscience or cognitive sciences.
Citations:
• Mikheev, V., Skukies, R., & Ehinger, B. V. (2024). The Art of Brainwaves: A survey on event-related potential visualization practices. Aperture Neuro, 4. https://doi.org/10.52294/001c.116386
• Mikheev, V., & Ehinger, B. V. (2025). UnfoldMakie.jl: EEG/ERP visualization package. Journal of Open Source Software, 10(105), 7560. https://doi.org/10.21105/joss.07560
