bioRxivNeurosciencePreprint
iBrAVE: a unified framework for 3D interactive and integrative analysis of brain atlas data across modalities and scales
Yufan WangiD, Ming-Quan Chen, Wei JiD, Hong-Bo Ma, Yongwei Zhong, Fu-Ning Li, Chenxi JiniD, Si-Xuan Cheng, Jia-Qi Guan, Yuan-Ming Zheng, Tian-Lei Zhang, Chao CheniD, Xiu-Dan Zheng, Shengjin XuiD, Kai WangiD, Jiulin DuiD, Xu-Fei DuiD
- Citations
- 2
Abstract
Understanding the brain requires integrating molecular, structural, and functional information across multiple scales. Despite the rapid expansion of multimodal, multiscale brain atlases in various species, integrative analysis remains challenging. Here, we present iBrAVE, an open-source platform for 3D interactive, integrative analysis of brain atlas datasets across modalities and scales within a common reference space. iBrAVE unifies heterogeneous datasets into five core representations, enabling source-independent analyses from insects to primates. At the single-modality level, it features spatially resolved quantification, as exemplified by single-neuron morphology analyses spanning geometry, topology, projection, clustering, and putative wiring. Across modalities, it links gene expression and neuronal activity with morphologically defined neurons and putative circuits via establishing spatial correspondence. Across scales, it enables bidirectional inference of neuronal identity and synaptic connectivity between light- and electron-microscopy reconstructions via neuronal morphology matching. Thus, iBrAVE provides a unified framework for integrative brain atlas analyses, facilitating data-driven discovery in neuroscience.
- organism: multiple species
- assay: spatial transcriptomics
- assay: imaging
- research focus: database / resource
- research focus: benchmarking
- research focus: dimensionality reduction
- research focus: clustering
- approach: experimental assay
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- multiVIB: A unified probabilistic contrastive learning framework for atlas-scale integration of single-cell multi-omics data
Yang Xu, Stephen J. Fleming, … Bing‐Xing Huo·bioRxiv·Nov 29, 2025
- Beyond Static Brain Atlases: AI-Powered Open Databasing and Dynamic Mining of Brain-Wide Neuron Morphometry
Shengdian Jiang, Lijun Wang, … Hanchuan Peng·Nature MethodsPeer-reviewed·Apr 29, 2025
- Solving the where problem in neuroanatomy: a generative framework with learned mappings to register multimodal, incomplete data into a reference brain
Daniel Jacob Tward, Bryson Gray, … Partha P. Mitra·bioRxiv·Mar 22, 2020
- Brainrender: a python-based software for visualizinganatomically registered data
Federico Claudi, Adam L. Tyson, … Tiago Branco·bioRxiv·Feb 23, 2020
- CynoBrain: A unified high-resolution framework for cross-modal data integration for macaque brain mapping
Hao Yang, Mingli Wang, … Zhifeng Liang·bioRxiv·Sep 13, 2026
- Siibra: A software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources
Timo Dickscheid, Xiaoyun Gui, … Katrin Amunts·Nature MethodsPeer-reviewed·Jul 20, 2026