Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion
Jiqing Wu, Ingrid Berg, Yawei Li, Ender Konukoglu, Viktor H. Koelzer
TL;DR
Tera-MIND is a novel 3D generative framework that simulates tera-scale mouse brains using spatial transcriptomic data, enabling detailed modeling of brain structures and molecular interactions at unprecedented scale.
Contribution
It introduces a patch-based, boundary-aware diffusion model for tera-scale brain simulation conditioned on spatial gene expression data, advancing computational modeling of complex brain structures.
Findings
Successfully generates detailed 3D mouse brain models at tera-scale.
Identifies spatial molecular interactions in key neural pathways.
Demonstrates applicability to human brain samples.
Abstract
Holistic 3D modeling of molecularly defined brain structures is crucial for understanding complex brain functions. Using emerging tissue profiling technologies, researchers charted comprehensive atlases of mammalian brain with sub-cellular resolution and spatially resolved transcriptomic data. However, these tera-scale volumetric atlases pose computational challenges for modeling intricate brain structures within the native spatial context. We propose \textbf{Tera-MIND}, a novel generative framework capable of simulating \textbf{Tera}-scale \textbf{M}ouse bra\textbf{IN}s in 3D using a patch-based and boundary-aware \textbf{D}iffusion model. Taking spatial gene expression as conditional input, we generate virtual mouse brains with comprehensive cellular morphological detail at teravoxel scale. Through the lens of 3D \textit{gene}-\textit{gene} self-attention, we identify spatial…
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Taxonomy
TopicsRNA Research and Splicing