Looks for topological pattern across axonal reconstructions without using any meta data, i.e. Allen labels, just based on data driven features.
Looks for topological pattern across axonal reconstructions without using any meta data, i.e. Allen labels, just based on data driven features.
We used 500 recons which was/is available at our website and that github repo has the code for that. Motivation was to see if we can get any pattern without using any meta data, just based on key features. In this case, features are generated from tip/junction locations (also Tiago generated nblast/Lmeasure for same purpose). For validation, we used Allen colors to see if they correlate.