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<p>Computational technology opens new possibilities toward understanding the complexity of the human brain, but it requires integrating measurements from different modalities and scales in an anatomical context and exposing them in an interoperable, actionable form. Especially with growing big data resources, accessing information from different scales and modalities coherently for visual exploration, reproducible analysis and application development remains challenging. Here we present siibra, a tool suite that connects diverse data from cloud resources to reference atlases and coordinate spaces. It supports different use cases by making contents accessible through a web viewer, Python library and HTTP application programming interface. Using siibra we implemented a Multilevel Human Brain Atlas linking macro-anatomical concepts and their inter-subject variability with measurements of the microstructural composition and intrinsic variance of brain regions, building on cytoarchitecture as a reference and supporting MRI-based and microscopic templates. The atlas is integrated with the EBRAINS research infrastructure. All software and content are openly accessible.</p>

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Siibra: a software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月20日

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  • Timo Dickscheid,
  • Xiaoyun Gui,
  • Ahmet N. Simsek,
  • Christian Schiffer,
  • Jean-Francois Mangin,
  • Yann Leprince,
  • Viktor Jirsa,
  • Jan G. Bjaalie,
  • Trygve B. Leergaard,
  • Sebastian Bludau,
  • Katrin Amunts

摘要

Computational technology opens new possibilities toward understanding the complexity of the human brain, but it requires integrating measurements from different modalities and scales in an anatomical context and exposing them in an interoperable, actionable form. Especially with growing big data resources, accessing information from different scales and modalities coherently for visual exploration, reproducible analysis and application development remains challenging. Here we present siibra, a tool suite that connects diverse data from cloud resources to reference atlases and coordinate spaces. It supports different use cases by making contents accessible through a web viewer, Python library and HTTP application programming interface. Using siibra we implemented a Multilevel Human Brain Atlas linking macro-anatomical concepts and their inter-subject variability with measurements of the microstructural composition and intrinsic variance of brain regions, building on cytoarchitecture as a reference and supporting MRI-based and microscopic templates. The atlas is integrated with the EBRAINS research infrastructure. All software and content are openly accessible.