biostudies-literatureDimmock SLeverhulme TrustMedical Research CouncilWellcome TrustBiotechnology and Biological Sciences Research CouncilEngineering and Physical Sciences Research CouncilRP102391https://www.ebi.ac.uk/biostudies/studies/S-EPMC12638045biostudies-literatureUnknown13We can now collect cell-count data across whole animal brains quantifying recent neuronal activity, gene expression, or anatomical connectivity. This is a powerful approach since it is a multiregion measurement, but because the imaging is done postmortem, each animal only provides one set of counts. Experiments are expensive, and since cells are counted by imaging and aligning a large number of brain sections, they are time-intensive. The resulting datasets tend to be undersampled with fewer animals than brain regions. As a consequence, these data are a challenge for traditional statistical approaches. We present a 'standard' partially pooled Bayesian model for multiregion cell-count data and apply it to two example datasets. These examples demonstrate that hierarchical Bayesian methods areLifeHierarchical Bayesian modeling of multiregion brain cell count data.PMC12638045BB/L02134X/1RF-2021-533MR/S026630/1206401/Z/17/ZEP/W024020/1BB/R007020/1EP/R513179/1Houghton CJO'Donnell CSchultz SRExley BMSMenage LMoore GWarburton ECDimmock SDelogu AfalseHierarchical Bayesian modeling of multiregion brain cell count data.We can now collect cell-count data across whole animal brains quantifying recent neuronal activity, gene expression, or anatomical connectivity. This is a powerful approach since it is a multiregion measurement, but because the imaging is done postmortem, each animal only provides one set of counts. Experiments are expensive, and since cells are counted by imaging and aligning a large number of brain sections, they are time-intensive. The resulting datasets tend to be undersampled with fewer animals than brain regions. As a consequence, these data are a challenge for traditional statistical approaches. We present a 'standard' partially pooled Bayesian model for multiregion cell-count data and apply it to two example datasets. These examples demonstrate that hierarchical Bayesian methods ar2025-01-01T00:00:00Z2025 Nov2026-06-05T17:07:43.148Z2026-05-19T03:12:03.578ZS-EPMC126380454126988110.7554/eLife.102391