# stMIND

Spatial transcriptomics sequencing is destructive, so each time point yields unaligned cell snapshots and the intermediate trajectories and cross-scale intercellular interactions stay unobserved. stMIND decomposes each cell's expression drift into a cell-intrinsic program, a local graph-difference operator over relative expression differences and spatial geometry within a radius, and a mass-weighted nonlocal mean-field attention operator outside it, with neighborhoods co-evolving as cells migrate. On axolotl telencephalon regeneration and zebrafish embryogenesis benchmarks it reaches the highest gene-expression accuracy, anatomical consistency and spatial coherence; ablations show both operators are needed, and the learned fields locate a regenerative transition at 10–15 days post-injury.

Spatial transcriptomics sequencing is destructive, so each time point yields unaligned cell snapshots and the intermediate trajectories and cross-scale intercellular interactions stay unobserved. stMIND decomposes each cell's expression drift into a cell-intrinsic program, a local graph-difference operator over relative expression differences and spatial geometry within a radius, and a mass-weighted nonlocal mean-field attention operator outside it, with neighborhoods co-evolving as cells migrate. On axolotl telencephalon regeneration and zebrafish embryogenesis benchmarks it reaches the highest gene-expression accuracy, anatomical consistency and spatial coherence; ablations show both operators are needed, and the learned fields locate a regenerative transition at 10–15 days post-injury.