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Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion

Abstract

Holistic 3D modeling of molecularly defined brain structures is crucial for understanding complex brain functions. Emerging tissue profiling technologies enable the construction of a comprehensive atlas of the mammalian brain with sub-cellular resolution and spatially resolved gene expression data. However, such tera-scale volumetric datasets present significant computational challenges in understanding complex brain functions within their native 3D spatial context. Here, we propose the novel generative approach Tera-MIND\textbf{Tera-MIND}, which can simulate Tera\textbf{Tera}-scale M\textbf{M}ouse braIN\textbf{IN}s in 3D using a patch-based and boundary-aware D\textbf{D}iffusion model. Taking spatial transcriptomic data as the conditional input, we generate virtual mouse brains with comprehensive cellular morphological detail at teravoxel scale. Through the lens of 3D genegene-genegene self-attention, we identify spatial molecular interactions for key transcriptomic pathways in the murine brain, exemplified by glutamatergic and dopaminergic neuronal systems. Importantly, these inin-silicosilico biological findings are consistent and reproducible across three tera-scale virtual mouse brains. Therefore, Tera-MIND showcases a promising path toward efficient and generative simulations of whole organ systems for biomedical research. Project website:this https URL

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@article{wu2025_2503.01220,
  title={ Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion },
  author={ Jiqing Wu and Ingrid Berg and Yawei Li and Ender Konukoglu and Viktor H. Koelzer },
  journal={arXiv preprint arXiv:2503.01220},
  year={ 2025 }
}
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