Exploring Kainic Acid-Induced Alterations in Circular Tripartite Networks with Advanced Analysis Tools

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computational Biology

Background:

• In vitro models are crucial for studying brain function and disease.
• Current models using human pluripotent stem cell-derived neuronal networks are evolving towards more complex brain-on-a-chip systems.
• These advanced models generate complex data requiring sophisticated analysis tools.

Purpose of the Study:

• To introduce advanced computational tools for analyzing electrophysiological data from circular tripartite neuronal networks.
• To assess synchronization and functional connectivity within these complex in vitro brain models.
• To evaluate the impact of kainic acid (KA) on neuronal network activity and its propagation.

Main Methods:

• Utilized a microfluidic device with separated neuronal networks and an embedded microelectrode array (circular tripartite network concept).
• Developed and applied custom analysis tools for synchronization and functional connectivity assessment.
• Applied kainic acid (KA) to a proximal compartment and monitored effects on distal compartments before and after exposure.

Main Results:

• Detected novel multilevel circuitry bursting patterns in response to KA.
• Quantified inter- and intracompartmental functional connectivity changes.
• Demonstrated the spread of KA-induced effects from the exposed proximal compartment to nonexposed distal compartments.
• Observed divergent changes in bursting behaviors linked to baseline activity and connectivity strengths.

Conclusions:

• The developed analysis tools significantly advance the assessment of brain-on-a-chip models.
• The circular tripartite network concept combined with advanced analysis improves the face and construct validity of in vitro epilepsy models.
• This approach offers a more accurate representation of human epilepsy in vitro.