Veneto, F. | bioRxiv Science

bioRxiv2026

Cholinergic and adrenergic modulation sculpts parallel inhibition of SST-INs in visual cortex

GABAergic interneurons are fundamental to the normal function of neuronal circuits in the neocortex. A growing literature has highlighted the role of somatostatin-expressing interneurons (SST-INs) in regulating cortical activity, and inhibition of SST-INs by other interneurons has emerged as a circuit motif leading to disinhibition of pyramidal neurons. However, the diversity and regulation of GABAergic inputs to SST-INs are only partially understood. Here, we combined widefield and 2-photon optogenetic stimulation of parvalbumin (PV)- and vasoactive intestinal peptide (VIP)-expressing interneurons with recordings from fluorescently identified SST-INs in layer 2/3 of primary visual cortex (V1). Our results show that both PV- and VIP-INs form inhibitory inputs onto SST-INs but with varying functional properties. PV-INs evoke strong, fast inhibition onto perisomatic regions of their target cells, while VIP-INs evoke slower inhibition onto target cell dendrites that is partially mediated by alpha subunit-containing GABA receptors. Cholinergic modulation through muscarinic receptors strongly suppresses PV-IN output while adrenergic modulation through beta receptors enhances VIP-IN output. Computational modeling suggests that these parallel inhibitory pathways can differentially regulate circuit gain and network stability across different inputs and arousal conditions. Thus, the diversity of disinhibitory GABAergic circuits in the neocortex provides a mechanism for state-dependent flexibility in circuit function.

neuroscience↗

bioRxiv2025

Cell-type-specific synaptic scaling mechanisms differentially contribute to associative learning

Excitatory synaptic scaling regulates network dynamics by proportionally adjusting excitatory synaptic strengths after sensory perturbations. During associative learning, blocking excitatory scaling in conditioned taste aversion paradigms prolongs generalized aversive responses and delays memory specificity. Recent evidence also implicates inhibitory synaptic scaling in the regulation of network dynamics. Specifically, parvalbumin (PV)-expressing inhibitory neurons, targeting perisomatic regions of excitatory (E) pyramidal neurons, and somatostatin (SST)-expressing neurons, targeting distal dendrites, exhibit distinct scaling responses. This leaves open the question of how complex plasticity mechanisms regulate recurrent excitatory-inhibitory circuit dynamics in associative learning. Using computational approaches, we demonstrate that Hebbian plasticity drives memory generalization to novel stimuli not presented during conditioning. Following conditioning, diverse synaptic scaling mechanisms progressively induce memory specificity, which can be regulated by top-down inputs. Our results reveal that, in the absence of excitatory scaling, PV-to-E scaling can effectively compensate and rescue memory specificity, highlighting the presence of degenerate mechanisms in the brain. Notably, in the process of establishing memory specificity, excitatory scaling and PV-to-E scaling function synergistically, while concurrently opposing SST-to-E scaling. The synergistic and antagonistic plasticity mechanisms are orchestrated to shape the temporal evolution of memory representations, from generalized to precise. Significance statementAssociative learning is a fundamental brain function that allows us to link experiences, adapt behavior, and form lasting memories. During this process, memory representations are shaped by synaptic scaling, a homeostatic plasticity mechanism that provides slow, negative feedback to regulate synaptic strengths and adjust network excitability. Operating at the synapses of diverse excitatory and inhibitory cell types, multiple forms of homeostatic plasticity influence the dynamics of associative learning. Here, we demonstrate that synergistic and antagonistic cell-type-specific synaptic scaling mechanisms operate at different types of inhibitory synapses to jointly govern the temporal evolution of memory representations. Through their interaction, they guide the transition from generalized to precise memories.

neuroscience↗