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Updated: Feb 3, 2026

Automated Detection and Analysis of Exocytosis
Published on: September 11, 2021
SICT: automated detection and supervised inspection of fast Ca2+ transients
Roberta Mancini1, Tobias van der Bijl1, Quentin Bourgeois-Jaarsma1
1Department of Functional Genomics, Faculty of Science, Center for Neurogenomics and Cognitive Research, Vrije Universiteit, De Boelelaan 1085, 1081HV, Amsterdam, The Netherlands.
Abstract:
Recent advances in live Ca2+ 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 Ca2+ 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 Ca2+ transients in the presence of caffeine. This new method speeds up the analysis of elementary Ca2+ transients.
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