摘要：The article discusses an approach to fluorescence microscopy using single-photon miniature fluorescence microscopes. The use of miniscopes allows you to expand the possibilities of their usage and solve many problems related to the need of fixing experimental material, insufficient scanning speed, complexity and high cost of usage. The authors developed a unique algorithm of correlations building based on cross-correlation of neuronal signals and implemented the opportunity to import experiment’s data in csv format. (as well as a utility for converting data from CNMF-E), which allows to import data from other sources. Special attention is paid to the methods of processing neural activity data: filtering the received frames from noise, compensating of image shifts and distortions.
