BrAVe: a unified framework for 3D interactive and integrative analysis of cross-modal multi-scale brain atlas data in diverse species

The brain exhibits remarkable complexity across molecular, structural, and functional modalities spanning spatial scales from micro- to macro-levels^1-3. Recent advances in brain mapping have yielded increasingly sophisticated multimodal, multi-scale atlases in diverse species^4-26. However, integrative analysis across these modalities and scales remains hindered by methodological and tool limitations²⁷. Here, we present BrAVe (BrainAtlas Viewer), an open-source, species-agnostic framework for 3D visualized and integrative analysis of brain atlas data across modalities and scales. BrAVe supports five core data types--volumetric images, parcellated regions, feature points, neuronal tracings, and networks--in standard formats (e.g., .nrrd, .stl, .csv., and .swc), accommodating multimodal and multi-scale datasets from flies to primates. For single-modality datasets, BrAVe provides a suite of analyses, with regional distribution profiling as a common feature. This is exemplified by its single-neuron morphology analysis, which enables quantitative characterization of geometry, topology, projection, clustering, and putative wiring. For multimodal datasets, BrAVe establishes spatially resolved correspondence across modalities within a common reference space, allowing the identification of molecularly defined neurons and the discovery of functionally associated circuits. BrAVe further bridges scales by matching neuronal reconstructions from light microscopy (LM) and electron microscopy (EM), enabling assignment of LM neuronal types for EM datasets, and leveraging EM synaptic connectivity to refine mesoscale wiring. Additional features include 3D image registration, scalable client-server data handling, and export of static and animated outputs. Combined with its intuitive interface and species compatibility, BrAVe offers a unified solution for integrative analysis of brain atlas datasets and empowers data-driven discovery in neuroscience research.