Figure 7

Schematic representation of MATLAB based algorithm for image analysis. (A) The maximum z-projection is calculated for each z-stack, then the background level is automatically retrieved and subtracted. The neurite structure mask is de-fined and applied as a filter to exclude unwanted signals located not in neurite structures. (B) An iterative thresholding procedure is used to binarized the image. Starting from the threshold value Thr = 0.2 (20% of the maximum signal) at each iteration, the threshold limit is increased by 0.15 units. The entire threshold image collection is combined to get a well-resolved binarized image. (C) The colocalization of the probe (BT1) with the antibodies (T22 and AT8) is calculated. Two well-known colocalization methods are exploited: the scatter plots (orange and green), which allow visualizing the correlation measured by PC coefficient, and the merged binary images (red/yellow and green/yellow), which allow to visualize the co-occurrence measured by M1 coefficient. (Matlab software, version 2021a; URL: https://it.mathworks.com/products/matlab.html?s_tid=hp_products_matlab).