Transcriptomics has revealed the exquisite diversity of cortical inhibitory neurons, but it is not known whether these fine molecular subtypes have correspondingly diverse activity patterns in the living brain. Here, we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, but that this diversity is organized by a single factor: position along their main axis of transcriptomic variation. We combined in vivo 2-photon calcium imaging of mouse V1 with a novel transcriptomic method to identify mRNAs for 72 selected genes in ex vivo slices. We used previously-defined transcriptomic clusters (Tasic et al, Nature 2018) to classify inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 Families, 11 Types, and 35 Subtypes. Visual responses differed significantly only across Families, with the Sncg Family showing notable suppression by visual stimuli. Modulation by brain state differed at all hierarchical levels, but a cell type’s brain state modulation and correlations with simultaneously recorded cells could be largely predicted from a single transcriptomic axis, the first transcriptomic principal component. Inhibitory Subtypes that fired more in resting, oscillatory brain states had narrower spikes, lower input resistance, weaker adaptation, and less axon in layer 1 as determined in vitro (Gouwens et al Cell 2020); Subtypes firing more during arousal had the opposite properties. The former Subtypes express more inhibitory cholinergic receptors, and the latter more excitatory cholinergic receptors in single-cell data. Thus, a simple principle may largely explain how diverse inhibitory V1 Subtypes shape state-dependent cortical processing.

Kenneth D. Harris studied mathematics at Cambridge University, did a PhD in robotics at UCL, then moved to Rutgers University in the United States for postdoctoral work in neuroscience. Before returning to UCL in 2012, he was Associate Professor of Neuroscience at Rutgers, and Professor of Neurotechnology at Imperial College London. He is currently Professor of Quantitative Neuroscience in the UCL Institute of Neurology. Together with Matteo Carandini he directs the Cortexlab.