Abstract
Brain-on-chip (BoC) models are tools for reproducing the native microenvironment of neurons, in order to study the (patho)physiology and drug-response of the brain. Recent developments in BoC techniques focus on steering neurons in their activity via microfabrication and via computer-steered feedback mechanisms. These cultures are often studied through calcium imaging (CI), a method for visualizing the cellular activity through infusing cells with a fluorescent dye. CAlciumImagingAnalyser 2.0 (CALIMA 2.0) is an updated version of a software tool that detects and analyzes fluorescent signals and correlates cellular activity to identify possible network formation in BoC cultures. Using three previous published data sets, it was demonstrated that CALIMA 2.0 can analyze large data sets of CI-data and interpret cell activity to help study the activity and maturity of BoC cultures. Last, an analysis of the processing speed shows that CALIMA 2.0 is sufficiently fast to process data sets with an acquisition rate up to 5 Hz in real-time on a medium-performance computer.