(10/10) We would also like to thank @lcolladotor.bsky.social, Ryan Miller, and @nick-eagles.bsky.social. Please check out VisiumStitcher, doi:10.1186/s12864-024-10991-y, which facilitates integration of gene expression and images across multiple capture areas for a specific donor, as in our data.

(9/10) Thank you to ‪@lieberinstitute.bsky.social, NIDA, and all our collaborators who made this work possible. 🧑‍🔬 #NAcLIBD @svitlana-bach.bsky.social, @rphillips3.bsky.social, @alexisbattle.bsky.social, @martinowk.bsky.social, @stephaniehicks.bsky.social, @kr-maynard.bsky.social

(8/10) It also provides a foundation for future higher-resolution investigation into NAc architecture, and serves as a key spatial atlas that can be integrated with functional data to better understand how the NAc mediates complex behaviors and risk for traits like substance dependence.

(7/10) Our work provides insights into how the structural organization of the human NAc shapes neuromodulatory signaling, opioid sensitivity, and links to neuropsychiatric risk.

(6/10) You can interactively explore our data at research.libd.org/spatial_NAc/... 💻 🔓 #opendata

(5/10) We illustrate the importance of spatial transcriptomics in understanding cell-cell communication, and identify spatial domains that express PENK, PDYN (ligands) and OPRM1 (receptor), and delineate the spatial distribution of their corresponding predicted sender and receiver cell types.

(4/10) We examine heterogeneity in D1 islands using complementary computational methods, such as matrix factorization and cell type deconvolution, as well as experimental techniques like RNAscope smFISH.

(3/10) Additionally, we show that human NAc organization is not simply divided into “core” and “shell,” but instead reflects continuous spatial gradients of MSN subtypes linked to genetic risk for psychiatric and addiction-related traits.

(2/10) We identify 20 transcriptionally distinct cell types, including 6 subtypes of medium spiny neurons (MSNs), and 8 spatial domains conserved across species, including distinct OPRM1-expressing D1-islands, corresponding to opioid hotspots previously described in rodents and non-human primates.