SICT: automated detection and supervised inspection of fast Ca transients.

Recent advances in live Ca imaging with increasing spatial and temporal resolution offer unprecedented opportunities, but also generate an unmet need for data processing. Here we developed SICT, a MATLAB program that automatically identifies rapid Ca rises in time-lapse movies with low signal-to-noise ratios, using fluorescent indicators. A graphical user interface allows visual inspection of automatically detected events, reducing manual labour to less than 10% while maintaining quality control. The detection performance was tested using synthetic data with various signal-to-noise ratios. The event inspection phase was evaluated by four human observers. Reliability of the method was demonstrated in a direct comparison between manual and SICT-aided analysis. As a test case in cultured neurons, SICT detected an increase in frequency and duration of spontaneous Ca transients in the presence of caffeine. This new method speeds up the analysis of elementary Ca transients.