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  Visualizing anatomically registered data with brainrender

Claudi, F., Tyson, A. L., Petrucco, L., Margrie, T. W., Portugues, R., & Branco, T. (2021). Visualizing anatomically registered data with brainrender. eLife, 10: e65751. doi:10.7554/eLife.65751.

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Locator:
https://elifesciences.org/articles/65751 (Publisher version)
Description:
Open Access
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 Creators:
Claudi, Federico1, Author
Tyson, Adam L.1, Author
Petrucco, Luigi2, Author           
Margrie, Troy W.1, Author
Portugues, Ruben2, Author           
Branco, Tiago1, Author
Affiliations:
1external, ou_persistent22              
2Max Planck Research Group: Sensorimotor Control / Portugues, MPI of Neurobiology, Max Planck Society, ou_2054291              

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Free keywords: Life Sciences & Biomedicine - Other Topics;
 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.

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Language(s): eng - English
 Dates: 2021-03-19
 Publication Status: Issued
 Pages: 16
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000645062600001
DOI: 10.7554/eLife.65751
 Degree: -

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Title: eLife
Source Genre: Journal
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Affiliations:
Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 10 Sequence Number: e65751 Start / End Page: - Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X