An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data
Fig 10
Computing of signals close to the noise level.
a, Typical hippocampal neuron, loaded with calcium indicator. Two ROIs are indicated. b,c, Calcium traces representing the yellow and magenta ROI in a. Removal of extracellular calcium causes a decline in the calcium indicator signal. This correlates with a reduced number of computed activity events (red dots). d-e, Number of computed activity events are shown on the x,y-grid. Under calcium-free conditions (cyan), a low number of activity events was found in the signal trace. In the presence of extracellular calcium, more activity events are computed by the algorithm. Regions of activity are found in the soma, but also on distal neurites. g,h, Summary graphs for computed activity events and variance area. The virtual activity value has a strong discriminative power to describe the experimental situation (calcium-free versus calcium present). n = 164 ROIs, mean ± SEM; one way ANOVA (Kruskal-Wallis) followed by Dunn’s multiple comparison test; p-values: ** < 0.001; **** < 0.0001. i, Representative signal analysis (yellow ROI in a) with deconvolution (blue dots), template-matching (green dots), and our CWT-approach. Phases of homeostatic activity in presence of extracellular calcium are best described with help of template-matching and CWT-computation.