Automated Brain Mapping Tool Helps Scientists Accurately Identify Where They’re Looking in the Brain

Background: Reliable identification of brain regions in histologic mouse brain sections is essential for neuroanatomical, genomic and connectomic analyses but is often limited by human error and variability when using traditional atlases. Manual matching of experimental sections to reference atlases is particularly challenging when sectioning planes differ, highlighting the need for an automated and objective solution.

Hypothesis: This study hypothesized that an automated system, NeuroInfo, could accurately register experimental mouse brain sections to the Allen Mouse Brain Common Coordinate Framework version 3 (CCF v3) and delineate brain regions with accuracy comparable to expert manual annotations.

Methods: The authors developed NeuroInfo as a Windows-based C++ desktop application. The software uses a multi-stage, intensity-based 3D image registration algorithm to align two-dimensional experimental sections with the 3D CCF v3 reference atlas. Validation was performed on 60 coronal sections from 12 mouse brains prepared in two laboratories and imaged using fluorescence or bright-field microscopy. Section images were acquired using Neurolucida. Automatic delineations were compared with manual ones drawn using Stereo Investigator, using Dice coefficients, centroid distances and area overlap metrics.

Results: NeuroInfo achieved strong agreement with manual delineations for large or dorsal regions (Dice >0.7), moderate alignment for small or ventrolateral regions (0.5–0.7), and weak performance for small midline or non-neuronal areas (<0.5). Mean registration time per section was approximately 77 seconds, and imaging modality had no effect on accuracy.

Conclusions: NeuroInfo accurately and efficiently identifies most major mouse brain regions, providing an objective, automated tool for histologic image registration and region delineation that enhances reproducibility in mouse brain mapping.

Tappan SJ, Eastwood BS, O’Connor N, Wang Q, Ng L, Feng D, Hooks BM, Gerfen CR, Hof PR, Schmitz C, Glaser JR. Automatic navigation system for the mouse brain. J Comp Neurol 2019;527(13):2200-2211. doi: 10.1002/cne.24635.