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

26 S.

Publikationstyp: Preprint (noch nicht publizierte Dokumente)

Sprache: Englisch

Doi/URN: 10.1101/2025.05.20.655042

Volltext über DOI/URN

Geprüft:Bibliothek

Inhaltszusammenfassung


Computational technology opens new possibilities towards understanding the complexity of the human brain, but it requires integrating measurements from different modalities and scales in anatomical context and exposing them in 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. We present siibra, a tool sui...Computational technology opens new possibilities towards understanding the complexity of the human brain, but it requires integrating measurements from different modalities and scales in anatomical context and exposing them in 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. 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 API. 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.Competing Interest StatementThe authors have declared no competing interest.Helmholtz Association, InterLabs-0015, Portfolio theme Supercomputing and Modeling for the Human BrainDeutsche Forschungsgemeinschaft, https://ror.org/018mejw64, Priority Program 2041 (SPP 2041) Computational Connectomics, NFDI4BIOIMAGE (501864659)European Union, Horizon 2020 Research and Innovation Programme Grant agreement 945539 (HBP SGA3), Horizon 2020 Research and Innovation Programme Grant agreement 101058516 (EBRAIN-Health), Horizon Europe Programme Grant agreement 101147319 (EBRAINS 2.0 Project)» weiterlesen» einklappen

Autoren


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

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