Seize the Data: A User-Friendly GUI for High-Resolution Analysis of Seizure Dynamics in HD-MEA Recordings

High-density multi-electrode arrays (HD-MEAs) generate large, complex datasets that are challenging to efficiently manage and analyze with existing tools, especially in open-source environments. To address this, we developed the BYU Seizure and Analytics Tool (YSA), an open-source graphical user interface (GUI) built in Python and C++ for efficient analysis and visualization of HD-MEA recordings. The YSA features raster plots, automated discharge detection and tracking, downsampling, playback, and export functions, enabling streamlined workflows for large-scale neural data. We demonstrate the utility of the tool in the context of seizure and status epilepticus (SE)-like activity, highlighting how the YSA facilitates rapid exploration of the spatiotemporal dynamics in brain networks. This platform provides an accessible and practical solution for HD-MEA data analysis, supporting a range of neuroscience applications. Significance StatementHigh-density multi-electrode arrays (MEAs) generate rich spatiotemporal datasets ideal for studying complex brain dynamics such as seizure activity. However, the size and complexity of these data often pose challenges for efficient analysis and interpretation. We present the BYU Seizure and Analytics Tool (YSA), an open-source graphical interface for intuitive visualization and exploration of MEA data. YSA enables users to navigate activity across the entire brain slice, identify relevant patterns, and easily export subsets for targeted analyses such as individual discharges. By making high-density seizure data more accessible and actionable, YSA streamlines analysis workflows and supports deeper insights into the spatiotemporal dynamics underlying seizure initiation and propagation in models of status epilepticus, pharmacoresistant epilepsy, and broader neural activity.