No abstract

Somatostatin (SST) is a neuropeptide expressed in a major subtype of GABAergic interneurons in the cortex. Despite abundant expression of SST and its receptors, their modulatory function in cortical processing remains unclear. Here, we found that SST application in the primary visual cortex (V1) improves visual discrimination in freely moving mice and enhances orientation selectivity of V1 neurons. We also found that SST reduced excitatory synaptic transmission to parvalbumin-positive (PV+) fast-spiking interneurons but not to regular-spiking neurons. Last, using serial block-face scanning electron microscopy (SBEM), we found that axons of SST+ neurons in V1 often contact other axons that exhibit excitatory synapses onto the soma and proximal dendrites of the PV+ neuron. Collectively, our results demonstrate that the neuropeptide SST improves visual perception by enhancing visual gain of V1 neurons via a reduction in excitatory synaptic transmission to PV+ inhibitory neurons.

The striatum is critically involved in value-based decision making. However, it is unclear how striatal direct and indirect pathways work together to make optimal choices in a dynamic and uncertain environment. Here, we examined the effects of selectively inactivating D1 receptor (D1R)- or D2 receptor (D2R)-expressing dorsal striatal neurons (corresponding to direct- and indirect-pathway neurons, respectively) on mouse choice behavior in a reversal task with progressively increasing reversal frequency and a dynamic two-armed bandit task. Inactivation of either D1R- or D2R-expressing striatal neurons impaired performance in both tasks, but the pattern of altered choice behavior differed between the two animal groups. A reinforcement learning model-based analysis indicated that inactivation of D1R- and D2R-expressing striatal neurons selectively impairs value-dependent action selection and value learning, respectively. Our results suggest differential contributions of striatal direct and indirect pathways to two distinct steps in value-based decision making.