Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience

Author:

Abdellah Marwan1ORCID,Cantero Juan José García1,Guerrero Nadir Román1,Foni Alessandro1,Coggan Jay S1,Calì Corrado234,Agus Marco56,Zisis Eleftherios1,Keller Daniel1,Hadwiger Markus5,Magistretti Pierre J2,Markram Henry1,Schürmann Felix1

Affiliation:

1. Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva , Switzerland

2. Biological and Environmental Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal , Saudi Arabia

3. Neuroscience Institute Cavalieri Ottolenghi (NICO) Orbassano , Italy

4. Department of Neuroscience, University of Torino Torino , Italy

5. Visual Computing Center King Abdullah University of Science and Technology (KAUST) Thuwal , Saudi Arabia

6. College of Science and Engineering Hamad Bin Khalifa University Doha , Qatar

Abstract

Abstract   Ultraliser is a neuroscience-specific software framework capable of creating accurate and biologically realistic 3D models of complex neuroscientific structures at intracellular (e.g. mitochondria and endoplasmic reticula), cellular (e.g. neurons and glia) and even multicellular scales of resolution (e.g. cerebral vasculature and minicolumns). Resulting models are exported as triangulated surface meshes and annotated volumes for multiple applications in in silico neuroscience, allowing scalable supercomputer simulations that can unravel intricate cellular structure–function relationships. Ultraliser implements a high-performance and unconditionally robust voxelization engine adapted to create optimized watertight surface meshes and annotated voxel grids from arbitrary non-watertight triangular soups, digitized morphological skeletons or binary volumetric masks. The framework represents a major leap forward in simulation-based neuroscience, making it possible to employ high-resolution 3D structural models for quantification of surface areas and volumes, which are of the utmost importance for cellular and system simulations. The power of Ultraliser is demonstrated with several use cases in which hundreds of models are created for potential application in diverse types of simulations. Ultraliser is publicly released under the GNU GPL3 license on GitHub (BlueBrain/Ultraliser). Significance There is crystal clear evidence on the impact of cell shape on its signaling mechanisms. Structural models can therefore be insightful to realize the function; the more realistic the structure can be, the further we get insights into the function. Creating realistic structural models from existing ones is challenging, particularly when needed for detailed subcellular simulations. We present Ultraliser, a neuroscience-dedicated framework capable of building these structural models with realistic and detailed cellular geometries that can be used for simulations.

Funder

King Abdullah University of Science and Technology

Swiss Federal Institute of Technology Lausanne

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

Reference102 articles.

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