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

Abstract

Brain activity implies the orchestrated functioning of interconnected brain regions. Typical in vitro models aim to mimic the brain using single human pluripotent stem cell-derived neuronal networks. However, the field is constantly evolving to model brain functions more accurately through the use of new paradigms, e.g., brain-on-a-chip models with compartmentalized structures and integrated sensors. These methods create novel data requiring more complex analysis approaches. The previously introduced circular tripartite network concept models the connectivity between spatially diverse neuronal structures. The model consists of a microfluidic device allowing axonal connectivity between separated neuronal networks with an embedded microelectrode array to record both local and global electrophysiological activity patterns in the closed circuitry. The existing tools are suboptimal for the analysis of the data produced with this model. Here, we introduce advanced tools for synchronization and functional connectivity assessment. We used our custom-designed analysis to assess the interrelations between the kainic acid (KA)-exposed proximal compartment and its nonexposed distal neighbors before and after KA. Novel multilevel circuitry bursting patterns were detected and analyzed in parallel with the inter- and intracompartmental functional connectivity. The effect of KA on the proximal compartment was captured, and the spread of this effect to the nonexposed distal compartments was revealed. KA induced divergent changes in bursting behaviors, which may be explained by distinct baseline activity and varied intra- and intercompartmental connectivity strengths. The circular tripartite network concept combined with our developed analysis advances importantly both face and construct validity in modeling human epilepsy in vitro.