TY - JOUR T1 - A simple Ca<sup>2+</sup>-imaging approach to neural network analysis in cultured neurons JF - bioRxiv DO - 10.1101/2020.08.09.243576 SP - 2020.08.09.243576 AU - Zijun Sun AU - Thomas C. Südhof Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/11/18/2020.08.09.243576.abstract N2 - Background Ca2+-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-electrode arrays or sophisticated imaging. Although such approaches allow detailed network analyses, multi-electrode arrays lack single-cell precision, whereas optical physiology generally requires advanced instrumentation.New Method Here we developed a simple, stimulation-free protocol with associated Matlab algorithms that enables scalable analyses of network activity in cultured human and mouse neurons. The approach allows analysis of overall networks and single-neuron dynamics, and is amenable to scale-up for screening purposes.Results We validated the protocol by assessing human neurons with a heterozygous conditional deletion of Munc18-1, and mouse neurons with a homozygous conditional deletion of neurexins. The approach described here enabled identification of differential changes in these mutant neurons at the network level and of the amplitude and frequency of calcium peaks at the single-neuron level. These results demonstrate the utility of the approach.Comparison with existing method Compared with current imaging platforms, our method is simple, scalable, and easy to implement. It enables quantification of more detailed parameters than multi-electrode arrays, but does not have the resolution and depth of more sophisticated yet labour-intensive analysis methods, such as electrophysiology.Conclusion This method is scalable for a rapid assessment of neuronal function in culture, and can be applied to both human and mouse neurons. Thus, the method can serve as a basis for phenotypical analysis of mutations and for drug discovery efforts.Competing Interest StatementThe authors have declared no competing interest. ER -