The problem. The human dorsolateral prefrontal cortex has a clear laminar structure — cortical layers with distinct molecular identities. Recovering those layers de novo from spatial transcriptomics is an ideal test of whether a method can detect real spatial domains, because there’s a known ground-truth anatomy to check against. But you need a carefully annotated dataset to serve as that benchmark.

The idea. Maynard and colleagues profiled DLPFC sections with 10x Visium (the commercial descendant of Ståhl), manually annotated the cortical layers and white matter, and released it as a reference. It’s both a biological study of cortical spatial expression and — more consequentially for the field — a gold-standard labelled dataset for benchmarking spatial-domain detection.

Why it matters. This is the spatial equivalent of the airway or PBMC datasets: the labelled benchmark that spatial-clustering and domain methods (BANKSY from day 4, SpaGCN later today) are validated on. For STU work it’s doubly relevant — a Visium dataset with trustworthy layer annotations is exactly what you reach for to test whether a domain-finding tool actually recovers known biology. I’ve almost certainly seen figures built on it.

Verdict. Foundational as a benchmark resource; its layered cortex is a recurring proving ground. Read it to know the dataset behind the spatial-domain comparisons — and as a model of pairing real biology with reusable ground truth.