# DMC-BrainMap is an open-source, end-to-end tool for multi-feature brain mapping in different species

**Authors:** Felix Jung, Xiao Cao, Loran Heymans, Marie Carlén

PMC · DOI: 10.1016/j.crmeth.2026.101302 · Cell Reports Methods · 2026-02-09

## TL;DR

DMC-BrainMap is a user-friendly, open-source tool for mapping and analyzing brain data from multiple species, streamlining neuroscience research.

## Contribution

DMC-BrainMap introduces an end-to-end GUI-based solution for multi-feature brain mapping across species without requiring programming skills.

## Key findings

- DMC-BrainMap supports whole-brain analysis of anatomical data from mice, rats, and zebrafish.
- The tool enables segmentation, quantification, and visualization of diverse features like cell bodies and axonal densities.
- It improves rigor and reproducibility by eliminating the need for programming and proprietary software.

## Abstract

Rigid anatomical mapping is a necessity in current neuroscience research. Here, we introduce DMC-BrainMap, an open-source napari plugin designed as a user-friendly tool for streamlined processing and whole-brain analysis of anatomical data. Its core functionalities include all steps after image acquisition, i.e., preprocessing of images, registration of images to a reference atlas, segmentation of different anatomical features, and data analysis/visualization. DMC-BrainMap can be applied to histological data obtained from a variety of model organisms at different developmental stages to map a diverse range of features. We demonstrate the utility of DMC-BrainMap by mapping and quantifying the location of cell bodies, axonal densities, injection sites, optical fiber and Neuropixels tracts, (single-cell) spatial transcriptomics, as well as neuron morphology data in mice, rats, and zebrafish. By eliminating the need for programming by the user, DMC-BrainMap provides an easy-to-use tool for increased rigor, reproducibility, and data sharing in neuroscientific research involving animal models.

•DMC-BrainMap is a GUI-based, end-to-end software for mapping of anatomical data•DMC-BrainMap can be used to analyze data from a diverse range of model organisms•DMC-BrainMap allows users to segment, quantify, and visualize a variety of features

DMC-BrainMap is a GUI-based, end-to-end software for mapping of anatomical data

DMC-BrainMap can be used to analyze data from a diverse range of model organisms

DMC-BrainMap allows users to segment, quantify, and visualize a variety of features

Robust mapping of anatomical structures and/or experimental parameters is a central component of current neuroscience research. However, the process of mapping, analyzing, and visualizing anatomical data remains challenging. Existing tools offer mapping of a limited set of features and a restricted set of references spaces, cover only part of the mapping process, rely on multiple (proprietary) software, and can require extensive programming knowledge. To overcome these hurdles, we developed a free, open-source, easy-to-use, GUI-based tool for flexible mapping of anatomical coordinates of a diverse range of features, including cell bodies, axonal densities, and injection and recording sites, in a variety of model organisms.

In this study, Jung et al. present DMC-BrainMap, a software for performing mapping of anatomical data (e.g., cell bodies, axonal densities, injection sites, and optic fiber/Neuropixels probe tracts) from different species including mice, rats, and zebrafish into reference spaces.

## Linked entities

- **Species:** Mus musculus (taxon 10090), Rattus norvegicus (taxon 10116), Danio rerio (taxon 7955)

## Full-text entities

- **Species:** Mus musculus (house mouse, species) [taxon 10090], Rattus norvegicus (brown rat, species) [taxon 10116], Danio rerio (leopard danio, species) [taxon 7955]

## Full text

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## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12946748/full.md

## References

48 references — full list in the complete paper: https://tomesphere.com/paper/PMC12946748/full.md

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Source: https://tomesphere.com/paper/PMC12946748