This repository includes code and data used in U. Sümbül et al., ``Automated computation of arbor densities: a step toward identifying neuronal cell types,'' Frontiers in Neuroanatomy, 2014.
The arbor traces are based on the raw image stacks, except for two files which are based on a basic deformation of the volume, as indicated by the file names. For details, please refer to github.com/uygarsumbul/rgc, which contains neurons from a more heterogeneous dataset as well. The dataset used in this paper is a subset of that dataset. The traces use voxel coordinates where the voxel size is 0.4um x 0.4 um x 0.5 um. For trace files using physical coordinates, please see github.com/uygarsumbul/rgc.
The SAC surface files contain the automatically detected starburst amacrine cell arbor positions. The variable minmesh (maxmesh) contains the depth coordinate of the On (Off) SAC surface for each xy pair. The values are in pixel coordinates.
The reconstruction files contain the coordinates of the voxels belonging to the neurons and the depth profiles. The variable 'voxels' contains the physical coordinates of the voxels of the 3d trace-based reconstructions of the neurons. The values are in um, where the depth values (voxels(:,:,3)) use the common depth coordinate, for which the distance between the On (0um) and Off (12um) SAC surfaces is 12um, as described in the paper.
The variable 'zDstribution' contains the registered depth profile in the interval [-30um, 29.5um] with a step size of 0.5um. The sum of the variable gives the volume of the reconstruction in um^3.
Only the software that is not already posted in github.com/uygarsumbul/rgc is posted in this repository.
Genetic identities of neurons: Image100-XXX : BDa Image101-XXX : BDa
Image102-XXX : JAM-B Image104-XXX : JAM-B
Image120-XXX : W3 Image121-XXX : W3 Image122-XXX : W3