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.