Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion
Abstract
Tera-MIND uses a patch-based and boundary-aware diffusion model to generate teravoxel-scale virtual mouse brains from spatial transcriptomic data, enabling the study of molecular interactions at the cellular level.
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, which can simulate Tera-scale Mouse braINs in 3D using a patch-based and boundary-aware Diffusion 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 gene-gene self-attention, we identify spatial molecular interactions for key transcriptomic pathways in the murine brain, exemplified by glutamatergic and dopaminergic neuronal systems. Importantly, these in-silico 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: http://musikisomorphie.github.io/Tera-MIND.html{https}
Community
Website: https://musikisomorphie.github.io/Tera-MIND.html
Code: https://github.com/CTPLab/Tera-MIND
The generated mouse brain at the scale of 0.77 x 1012 voxels (Main result).
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