Exploring the Allen mouse connectivity experiments with new neuroinformatic tools for neurophotonics, diffusion MRI and tractography applications

International audienceThe Allen Mouse Brain Connectivity Atlas (AMBCA) o↵ers a high-resolution map of neural connections detailing axonal projections labeled by viral tracers. It is a unique tool for studying structural connectivity and better understanding the white matter pathways of the gene mouse brain. But, the analysis and comparison of these data are limited to a simple visualization on the Allen website and have no direct relationship with specific User data. Here, we propose a series of python-based tools to operate with AMBCA data in the User's data space. Our method is based on "back and forth" actions between Allen and User data using the Allen Software Development Kit (AllenSDK) to import data from the Allen Institute and the Python package ANTsPyX for registration. A transformation matrix is calculated with ANTsPyX to overlay, for instance, Allen's projection density maps with a di↵usion MRI-based tractography in the User space. Conversely, applying the inverse transformation to a specific location along a white matter bundle within the User space allows us to recover which experiments were done at this particular location in the Allen Mouse brain Common Coordinate Framework (CCFv3). Thus, both data can be used in a natural interaction, e.g., by inspecting them in a visualization tool such as the MI-Brain software. This series of tools will o↵er an attractive solution for researchers with neural tracing and/or tractography data to be combined with the AMBCA. The code is available at: https: //github.com/linum-uqam/m2m