Stochastic Simulation Model for Patterned Neural Multi-Electrode Arrays

A multi-electrode array (MEA) is a micro-fabricated cell culture dish with embedded microelectrodes at the bottom of the dish. Recently MEAs with different cell-adhesive patterns are actively used to analyze behaviors of in vitro neural systems. It is difficult to confirm the underlying anatomical synaptic connections of the in vitro neural networks based on neural recordings from MEAs. Meanwhile, computational modeling and simulation cannot only facilitate various in silico combinatorial stimulus-response analysis but also provide connection-aware analysis capability. Here we propose a simulation approach of encompassing the whole MEA experiments including cell seeding, axonal growth, network morphology and the recordings of the electrodes of MEAs. Cell densities and the geometry of network morphology could be varied systematically and multiple spike trains from the simulated networks were obtained.