Abstract

Microelectrode arrays (MEAs) are widely used to study neuronal function in vitro. These devices allow concurrent non-invasive recording/stimulation of electrophysiological activity for long periods. However, the property of sensing signals from all sources around every microelectrode can become unfavorable when trying to understand communication and signal propagation in neuronal circuits. In a neuronal network, several neurons can be simultaneously activated and can generate overlapping action potentials, making it difficult to discriminate and track signal propagation. Considering this limitation, we have established an in vitro setup focused on assessing electrophysiological communication, which is able to isolate and amplify axonal signals with high spatial and temporal resolution. By interfacing microfluidic devices and MEAs, we are able to compartmentalize neuronal cultures with a well-controlled alignment of the axons and microelectrodes. This setup allows recordings of spike propagation with a high signal-to-noise ratio over the course of several weeks. Combined with specialized data analysis algorithms, it provides detailed quantification of several communication related properties such as propagation velocity, conduction failure, firing rate, anterograde spikes, and coding mechanisms. This protocol demonstrates how to create a compartmentalized neuronal culture setup over substrate-integrated MEAs, how to culture neurons in this setup, and how to successfully record, analyze and interpret the results from such experiments. Here, we show how the established setup simplifies the understanding of neuronal communication and axonal signal propagation. These platforms pave the way for new in vitro models with engineered and controllable neuronal network topographies. They can be used in the context of homogeneous neuronal cultures, or with co-culture configurations where, for example, communication between sensory neurons and other cell types is monitored and assessed. This setup provides very interesting conditions to study, for example, neurodevelopment, neuronal circuits, information coding, neurodegeneration and neuroregeneration approaches.