NBLAST is an algorithm to quantify morphological similarity between neurons. Its second version (Costa et al., 2016) uses a 2D scoring matrix to determine whether two points (or rather the distance between them and the dot product of their vectors) are indicative of two neurons belonging to the same type or not.
The original scoring matrix was generated using neurons from the FlyCircuit project - i.e. Drosophila neurons skeletonized from confocal stacks co-registered to a template brain. Despite being created for fly neurons and from light-level data it works surprisingly well for other types of data (e.g. EM-derived skeletons) and organisms. That said: there is probably mileage in generating specialised scoring functions for certain applications.
This repository collects alternative scoring matrices that you can plug into e.g. the
Python implementation in navis or the R implementation in nat.
Contributions welcome!
scoremats/fcwb.csv is the original scoring matrix made from light-level data of Drosophila co-registered to the same template space.
scoremats/hemibrain.csv was generated from Drosophila neurons from the Janelia hemibrain connectome.
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