Hi!

The banding pattern in your pct_counts_mt plot is likely an artifact from the discrete nature of count data after Bin2Cell aggregation. Visium HD bins have low individual counts, and when grouped into cells, the mitochondrial reads (often sparse) result in small integer values for mt counts. This causes the percentages to cluster at specific intervals, appearing as bands in violin or density plots.

Check the distribution of raw mt counts per cell using something like hist(your_seurat_object@meta.data$nFeature_mt). If most cells have very low mt UMIs (e.g., 0-10), that explains the stepping effect, especially if total UMIs aren't high enough to smooth it out.

It's not uncommon in spatial data with binning—standard scRNA-seq usually has higher depth per cell. If it's bothering downstream analysis, you could filter cells with extreme low counts or adjust plot bandwidth in VlnPlot.

Hope this helps.

Kevin