Modeling and simulation of electrodiffusion in dense reconstructions of cerebral tissue
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866917121100873728 |
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| author | Herlyng, Halvor Causemann, Marius Einevoll, Gaute T. Ellingsrud, Ada J. Halnes, Geir Rognes, Marie E. |
| author_facet | Herlyng, Halvor Causemann, Marius Einevoll, Gaute T. Ellingsrud, Ada J. Halnes, Geir Rognes, Marie E. |
| contents | Excitable tissue is fundamental to brain function, yet its study is complicated by extreme morphological complexity and the physiological processes governing its dynamics. Consequently, detailed computational modeling of this tissue represents a formidable task, requiring both efficient numerical methods and robust implementations. Meanwhile, efficient and robust methods for image segmentation and meshing are needed to provide realistic geometries for which numerical solutions are tractable. Here, we present a computational framework that models electrodiffusion in excitable cerebral tissue, together with realistic geometries generated from electron microscopy data. To demonstrate a possible application of the framework, we simulate electrodiffusive dynamics in cerebral tissue during neuronal activity. Our results and findings highlight the numerical and computational challenges associated with modeling and simulation of electrodiffusion and other multiphysics in dense reconstructions of cerebral tissue. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_03224 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modeling and simulation of electrodiffusion in dense reconstructions of cerebral tissue Herlyng, Halvor Causemann, Marius Einevoll, Gaute T. Ellingsrud, Ada J. Halnes, Geir Rognes, Marie E. Medical Physics Numerical Analysis Excitable tissue is fundamental to brain function, yet its study is complicated by extreme morphological complexity and the physiological processes governing its dynamics. Consequently, detailed computational modeling of this tissue represents a formidable task, requiring both efficient numerical methods and robust implementations. Meanwhile, efficient and robust methods for image segmentation and meshing are needed to provide realistic geometries for which numerical solutions are tractable. Here, we present a computational framework that models electrodiffusion in excitable cerebral tissue, together with realistic geometries generated from electron microscopy data. To demonstrate a possible application of the framework, we simulate electrodiffusive dynamics in cerebral tissue during neuronal activity. Our results and findings highlight the numerical and computational challenges associated with modeling and simulation of electrodiffusion and other multiphysics in dense reconstructions of cerebral tissue. |
| title | Modeling and simulation of electrodiffusion in dense reconstructions of cerebral tissue |
| topic | Medical Physics Numerical Analysis |
| url | https://arxiv.org/abs/2512.03224 |