Chip characterization and database development for HD CMOS MEAs

Multi-electrode array (MEA) chips are rapidly growing as one of the main technologies to unveil complex electrophysiological dynamics of both cells and tissues. Because of their high density and resolution, MEA devices are ideal candidates to record and stimulate single cells in culture. Nevertheless, packaging approaches that protect electronic components from harsh biological environments and allow for long-term device usage remain undressed. Further, the correct addressability of each individual electrode is a major importance to enable correlation between MEA measurements and microscopy. The first part of this thesis was focused on assessing long term stability of the devices and characterizing chip performance. However, as the global pandemic constrained experimental work to a minimum, the thesis was complemented with a second part, the development of a database that could be conducted complying with the restrictions. During part one, we focused on assessing different packaging approaches performed by an external company. Here we found that while the packaging approach did not have an effect on the chip performance, the wire bonding was incorrectly performed and the yield of functional chips was 34%. Later, we tested a second batch were special attention to the wire bonding technique was paid and the chip yield increased to 80%. Additionally, we developed an assay based on pH imaging to assess the correct addressability of electrodes during chip programming. We concluded that while the programming is correctly implemented, chip manufacturing variabilities can cause unwanted electrodes to be addressed. Part two consisted of designing and developing a database to log chip packaging and performance information in a user-friendly and accessible manner. This implementation allowed the users to reduce the time spent logging in information and provided a clear overview on chip availability and usage. In conclusion, the work presented here paved the way toward a more robust platform by providing tools to assure correct functionality as well as improving material and experiment tracking.