An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data
Fig 2
Calcium activity assessment with the activity detector tool.
a, Principle of calcium activity event detection. Activity event identification is shown for a representative grid window (per se representing a ROI) on a single motoneuron. This motoneuron (shown in the inlet, and in Fig 1) shows global calcium transients. 2600 images (frames; x-axis) were analyzed. The grey trace shows the raw mean intensity values of a representative grid window. After extraction of the image signal in a grid window, all local maxima of the intensity signal are identified at several scales (y-axis) and signal candidates are selected and marked (blue dots). Details are explained in the methods: Strategy for calcium event (peak) identification. b, Effect of tuning parameters on calcium activity event detection. The total number of computed activity events (y-axis) in relation to changes in the user-dependent signal-to-noise ratio (SNR). Two activity stages of the motoneuron are compared. The low activity state (in a, frame 1–1300) and the high activity state (frame 1301–2600). Discrimination of the high activity state and the low activity state is very effective over a broad range of SNR values from 1.5 to 4. The signal average threshold was set to an intensity value of 6 (up-rounded mean intensity value seen in the background). A conservative SAT value was selected and modified at a SNR of 2 (blue square; SAT = 5 a.u.; purple circle; SAT = 6 a.u.). c, Data documentation 1: x,y-t summary. The image shows the distribution and number of calcium activity events raised by a spontaneously active motoneuron. Such an image is automatically generated by the program. The user-dependent tuning parameters for this analysis are given. The image field 142 x 130 pixel was automatically split in a grid of 8 x 8 pixel (WS 8 px). Magenta circles indicate areas with calcium events. The smaller the diameter, the less activity is found in the corresponding grid window. All detected calcium activity events are summed up to offer the value ‘total activity’. d, Data documentation 2: the individual traces represent changes in fluorescence in one grid window. The tool automatically generates traces (black line) representing a grid window and shows raw bit values (y-axis) over the frame number (x-axis). Calcium activity events detected by the tool are labeled with a little red square at the peak point. The upper panel describes the graph in grid 5/14 (x/y-axis) in the somatic region of the motoneuron. Here raw bit values ranged from about 65 to 110. In the lower panel a region in the growth cone of the motoneuron was analyzed (grid 13/4; x/y-axis). Here, raw mean bit values in the grid range from 6 to 10. Note the robust detection of global activity despite an almost 10-fold difference in the mean intensity values in the corresponding grid window.