Visualizing Anatomically Registered Data with Brainrender

Overview

Journal Elife

Specialty Biology

Date 2021 Mar 19

PMID 33739286

Citations 55

Authors

Federico Claudi

Adam L Tyson

Luigi Petrucco

Troy W Margrie

Ruben Portugues

Tiago Branco

Affiliations

Soon will be listed here.

Abstract

Three-dimensional (3D) digital brain atlases and high-throughput brain-wide imaging techniques generate large multidimensional datasets that can be registered to a common reference frame. Generating insights from such datasets depends critically on visualization and interactive data exploration, but this a challenging task. Currently available software is dedicated to single atlases, model species or data types, and generating 3D renderings that merge anatomically registered data from diverse sources requires extensive development and programming skills. Here, we present brainrender: an open-source Python package for interactive visualization of multidimensional datasets registered to brain atlases. Brainrender facilitates the creation of complex renderings with different data types in the same visualization and enables seamless use of different atlas sources. High-quality visualizations can be used interactively and exported as high-resolution figures and animated videos. By facilitating the visualization of anatomically registered data, brainrender should accelerate the analysis, interpretation, and dissemination of brain-wide multidimensional data.

Citing Articles

Brain-wide mapping reveals temporal and sexually dimorphic opioid actions.

Vasylieva I, Smith M, Aravind E, He K, Ling T, Kozel J bioRxiv. 2025; .

PMID: 40060548 PMC: 11888231. DOI: 10.1101/2025.02.19.638902.

An opponent striatal circuit for distributional reinforcement learning.

Lowet A, Zheng Q, Meng M, Matias S, Drugowitsch J, Uchida N Nature. 2025; .

PMID: 39972123 DOI: 10.1038/s41586-024-08488-5.

Classification of psychedelics and psychoactive drugs based on brain-wide imaging of cellular c-Fos expression.

Aboharb F, Davoudian P, Shao L, Liao C, Rzepka G, Wojtasiewicz C Nat Commun. 2025; 16(1):1590.

PMID: 39939591 PMC: 11822132. DOI: 10.1038/s41467-025-56850-6.

A deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy.

Attarpour A, Osmann J, Rinaldi A, Qi T, Lal N, Patel S Nat Methods. 2025; 22(3):600-611.

PMID: 39870865 PMC: 11903318. DOI: 10.1038/s41592-024-02583-1.

Molecular logic for cellular specializations that initiate the auditory parallel processing pathways.

Jing J, Hu M, Ngodup T, Ma Q, Lau S, Ljungberg M Nat Commun. 2025; 16(1):489.

PMID: 39788966 PMC: 11717940. DOI: 10.1038/s41467-024-55257-z.

References

Renier N, Adams E, Kirst C, Wu Z, Azevedo R, Kohl J . Mapping of Brain Activity by Automated Volume Analysis of Immediate Early Genes. Cell. 2016; 165(7):1789-1802. PMC: 4912438. DOI: 10.1016/j.cell.2016.05.007. View

Tyson A, Rousseau C, Niedworok C, Keshavarzi S, Tsitoura C, Cossell L . A deep learning algorithm for 3D cell detection in whole mouse brain image datasets. PLoS Comput Biol. 2021; 17(5):e1009074. PMC: 8191998. DOI: 10.1371/journal.pcbi.1009074. View

Young D, Duhn C, Gilson M, Nojima M, Yuruk D, Kumar A . Whole-Brain Image Analysis and Anatomical Atlas 3D Generation Using MagellanMapper. Curr Protoc Neurosci. 2020; 94(1):e104. PMC: 7781073. DOI: 10.1002/cpns.104. View

Chon U, Vanselow D, Cheng K, Kim Y . Enhanced and unified anatomical labeling for a common mouse brain atlas. Nat Commun. 2019; 10(1):5067. PMC: 6838086. DOI: 10.1038/s41467-019-13057-w. View

Bates A, Manton J, Jagannathan S, Costa M, Schlegel P, Rohlfing T . The natverse, a versatile toolbox for combining and analysing neuroanatomical data. Elife. 2020; 9. PMC: 7242028. DOI: 10.7554/eLife.53350. View

Ascoli G, Donohue D, Halavi M . NeuroMorpho.Org: a central resource for neuronal morphologies. J Neurosci. 2007; 27(35):9247-51. PMC: 6673130. DOI: 10.1523/JNEUROSCI.2055-07.2007. View

Winnubst J, Bas E, Ferreira T, Wu Z, Economo M, Edson P . Reconstruction of 1,000 Projection Neurons Reveals New Cell Types and Organization of Long-Range Connectivity in the Mouse Brain. Cell. 2019; 179(1):268-281.e13. PMC: 6754285. DOI: 10.1016/j.cell.2019.07.042. View

Simmons D, Swanson L . Comparing histological data from different brains: sources of error and strategies for minimizing them. Brain Res Rev. 2009; 60(2):349-67. PMC: 2680454. DOI: 10.1016/j.brainresrev.2009.02.002. View

Steinmetz N, Zatka-Haas P, Carandini M, Harris K . Distributed coding of choice, action and engagement across the mouse brain. Nature. 2019; 576(7786):266-273. PMC: 6913580. DOI: 10.1038/s41586-019-1787-x. View

10.

. A multimodal cell census and atlas of the mammalian primary motor cortex. Nature. 2021; 598(7879):86-102. PMC: 8494634. DOI: 10.1038/s41586-021-03950-0. View

11.

Jin M, Nguyen J, Weber S, Mejias-Aponte C, Madangopal R, Golden S . SMART: An Open-Source Extension of WholeBrain for Intact Mouse Brain Registration and Segmentation. eNeuro. 2022; 9(3). PMC: 9070730. DOI: 10.1523/ENEURO.0482-21.2022. View

12.

Kunst M, Laurell E, Mokayes N, Kramer A, Kubo F, Fernandes A . A Cellular-Resolution Atlas of the Larval Zebrafish Brain. Neuron. 2019; 103(1):21-38.e5. DOI: 10.1016/j.neuron.2019.04.034. View

13.

Wang Q, Ding S, Li Y, Royall J, Feng D, Lesnar P . The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas. Cell. 2020; 181(4):936-953.e20. PMC: 8152789. DOI: 10.1016/j.cell.2020.04.007. View

14.

Lein E, Hawrylycz M, Ao N, Ayres M, Bensinger A, Bernard A . Genome-wide atlas of gene expression in the adult mouse brain. Nature. 2006; 445(7124):168-76. DOI: 10.1038/nature05453. View

15.

Harris C, Millman K, van der Walt S, Gommers R, Virtanen P, Cournapeau D . Array programming with NumPy. Nature. 2020; 585(7825):357-362. PMC: 7759461. DOI: 10.1038/s41586-020-2649-2. View

16.

Ding S, Royall J, Sunkin S, Ng L, Facer B, Lesnar P . Comprehensive cellular-resolution atlas of the adult human brain. J Comp Neurol. 2016; 524(16):3127-481. PMC: 5054943. DOI: 10.1002/cne.24080. View

17.

Arganda-Carreras I, Manoliu T, Mazuras N, Schulze F, Iglesias J, Buhler K . A Statistically Representative Atlas for Mapping Neuronal Circuits in the Adult Brain. Front Neuroinform. 2018; 12:13. PMC: 5876320. DOI: 10.3389/fninf.2018.00013. View

18.

Furth D, Vaissiere T, Tzortzi O, Xuan Y, Martin A, Lazaridis I . An interactive framework for whole-brain maps at cellular resolution. Nat Neurosci. 2017; 21(1):139-149. PMC: 5994773. DOI: 10.1038/s41593-017-0027-7. View

19.

Song J, Choi W, Song Y, Kim J, Jeong D, Lee S . Precise Mapping of Single Neurons by Calibrated 3D Reconstruction of Brain Slices Reveals Topographic Projection in Mouse Visual Cortex. Cell Rep. 2020; 31(8):107682. DOI: 10.1016/j.celrep.2020.107682. View

20.

Mathis A, Mamidanna P, Cury K, Abe T, Murthy V, Mathis M . DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat Neurosci. 2018; 21(9):1281-1289. DOI: 10.1038/s41593-018-0209-y. View