Hi Lydia (I am assuming, maybe wrongly, that you are Lydia Ng),

Many thanks for your answer. I was particularly interested in the flatenning process that produced the files `dorsal_flatmap_paths_100.h5`

and `top_view_paths_100.h5`

.

I realized that I forgot to attach to my question this piece of information that I already reported in the github issue. We have now some insight on the process, see the quoted text below, but I was very curious about the implementation details (Which libraries have been used? Is it a volume-based or mesh-based approach? Is the code, or some parts of it, publically available?).

**Information on the flattening process reported in https://github.com/AllenInstitute/mouse_connectivity_models/issues/44:**

Thanks to a colleague of mine, Sirio Puchet (Blue Brain Project), I have now more insight on this question. Indeed, Sirio pointed out that some details on the flattening process are available in the section **Creation of the cortical top-down and flattened views of the CCFv3 for data visualization** of **Hierarchical organization of cortical and thalamic connectivity** (https://www.nature.com/articles/s41586-019-1716-z):

A cortical flatmap was also constructed to enable visualization of anatomical and projection information while preserving spatial context for the entire cortex. The flatmap was created by computing the geodesic distance (the shortest path between two points on a curve surface) between every point on the cortical surface and two pairs of selected anchor points. Each pair of anchor points forms one axis of the 2D embedding of the cortex into a flatmap. The 2D coordinate for each point on the cortical surface is obtained by finding the location such that the radial (circular) distance from the anchor points (in 2D) equals the geodesic distance that was computed in 3D. This procedure produces smooth mapping of the cortical surface onto a 2D plane for visualization. This embedding does not preserve area and the frontal pole and medial-posterior region is highly distorted. As such, all numerical computation is done in 3D space. Similar techniques are used for texture mapping on geometric models in the field of computer [57].

[57] Oliveira, G. N., Torchelsen, R. P., Comba, J. L. D., Walter, M. & Bastos, R. Geotextures: a multi-source geodesic distance field approach for procedural texturing of complex meshes. 2010 23rd SIBGRAPI Conf. Graphics, Patterns and Images 126–133 (IEEE, 2010).