Structured Inhibitory Activity Dynamics During Learning

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Abstract
Hippocampal network activity is tightly regulated by local inhibitory interneurons. Suppression of inhibition has been proposed to accelerate learning by enhancing network activity and plasticity; however, the activity dynamics of hippocampal interneurons during learning remain poorly understood. Furthermore, it is unknown if individual interneurons are stochastically suppressed across different learning episodes, mirroring the random remapping of place cells, or if instead they exhibit consistent patterns of activity suppression. These critical properties define how inhibition shapes and controls learning at a network level. To uncover the functional circuit dynamics of inhibition during novelty-induced learning, we recorded calcium activity from hippocampal CA1 interneurons using two-photon imaging as mice learned a virtual reality (VR) goal-directed spatial navigation task in new visual contexts. Here we focused on dendrite-targeting somatostatin-expressing interneurons (SOM-ints), which powerfully control burst firing and synaptic plasticity in excitatory neurons. We found robust activity suppression in SOM-ints upon exposure to novel virtual environments; activity then recovered over repeated exposures to the novel environment as the animal learned goal locations. At a population level, we found a continuum of activity suppression, from interneurons strongly suppressed to moderately activated during learning. Surprisingly, each interneuron exhibited a stable level of activity modulation: when animals were switched into a second novel environment, the magnitude of activity suppression was strongly correlated across remapping sessions. This work reveals dynamic inhibition suppression triggered by novel environments and the gradual return of inhibition with learning. Furthermore, unlike the stochastic remapping of place cells, inhibitory networks display a stable activity structure across learning episodes. This functional inhibitory circuit architecture suggests that individual interneurons play specialized and stereotyped roles during learning, perhaps by differentially regulating pyramidal subnetworks specialized for plasticity and stability.
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