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

Area of Science:

• Neuroscience
• Computational Neuroscience
• Bioinformatics

Background:

• High-density multielectrode arrays (HD-MEAs) generate vast datasets that pose significant challenges for current data management and analysis tools.
• Existing analytical tools often lack efficiency and accessibility, particularly within open-source research environments.

Purpose of the Study:

• To develop an efficient, open-source graphical user interface (GUI) for analyzing and visualizing large, complex datasets from HD-MEA recordings.
• To provide a streamlined workflow for handling and interpreting large-scale neural data, specifically focusing on seizure and status epilepticus-like activity.

Main Methods:

• Development of the BYU Seizure and Analytics Tool (YSA) using Python and C++.
• Implementation of features including raster plots, automated discharge detection and tracking, data downsampling, playback, and export functionalities.
• Demonstration of the YSA's utility in analyzing spatiotemporal dynamics of brain networks during seizure activity.

Main Results:

• The YSA provides efficient analysis and visualization capabilities for HD-MEA data.
• Automated detection and tracking of neural discharges are facilitated by the tool.
• The YSA enables rapid exploration of spatiotemporal dynamics in brain networks, particularly for seizure-like events.

Conclusions:

• The YSA offers an accessible and practical solution for the analysis of HD-MEA data.
• This open-source platform supports various neuroscience applications by streamlining complex neural data workflows.
• The tool is particularly effective for studying the dynamics of seizure and status epilepticus-like activity in neural networks.