A high-dimensional atlas of parvalbumin interneuron soma morphology in mouse visual and somatosensory cortex

Parvalbumin-positive (PV+) inhibitory interneurons are central components of experience-dependent plasticity in the visual cortex (V1). Anatomically, they are distributed across cortical layers and are traditionally classified as basket, chandelier, or bipolar cells based on dendritic and axonal arborization patterns. In parallel, physiological, transcriptomic, connectomic, and multimodal studies have revealed substantial diversity within PV+ populations, raising the question of how this diversity is organized within cortical circuits. In contrast, light microscopy studies based on soma labeling have primarily quantified PV+ cells using size and density, and the potential of soma morphology to capture this diverse organization remains unclear. To address this, we developed a high-throughput, data-driven approach to quantify PV+ soma morphology in > 14,000 cells from mouse V1 and somatosensory cortex (S1). Using 97 morphological features combined with clustering, phenotyping, and laminar mapping, we identified structured diversity in PV+ somas. PV+ cells were organized into 13 morphological clusters along partially independent gradients of size and shape. Phenotyping identified four size and five shape categories that describe PV+ cell diversity across cortical areas. Mapping these categories onto cortical layers revealed a structured organization in which specific morphologies are enriched within distinct laminar compartments. This organization aligns with cortical architecture and suggests that PV+ interneuron morphology is systematically related to circuit structure. These findings demonstrate that substantial morphological information can be extracted from standard PV+ labeling approaches using quantitative analysis. Together, this work provides a high-dimensional atlas of PV+ interneuron soma morphology in mouse V1 and S1 and establishes a framework for linking cellular anatomy to circuit organization and experience-dependent plasticity.