Abstract
Somatostatin (SST)-expressing inhibitory neurons are a major class of neocortical γ-aminobutyric acid neurons, where morphological, electrophysiological, and transcriptomic analyses indicate more than a dozen different subtypes. However, whether this diversity is related to specific roles in cortical computations and plasticity remains unclear. Here, we identify learning-dependent, subtype-specific plasticity in layer 2/3 SST neurons of the mouse somatosensory cortex. Martinotti-type, SST neurons expressing calbindin-2 show a selective decrease in excitatory synaptic input and stimulus-evoked calcium responses, as mice learn a stimulus-reward association. Using these insights, we develop a label-free classifier using basal activity from in vivo imaging that accurately predicts learning-associated response plasticity. Our data indicate that molecularly defined SST neuron subtypes play specific and highly regulated roles in sensory information processing and learning.