Inhgrams for engrams: co-active inhibitory-inhibitory plasticity shapes inhibitory assemblies that stabilize and recall embedded engrams through disinhibition

Abstract

Inhibitory neurons have been widely understood to play a supporting role in neural function and memory formation, but recent advances highlight that memories are encoded by both excitatory and inhibitory neurons (EI assemblies), carving out a bigger role for inhibition beyond mere stabilization. However, the computations enabled by such EI assemblies are still unclear, and the synaptic plasticity rules that could sustain and retrieve memories are unknown. Here, we construct a computational model for EI assembly recall and investigate the computational benefits of such mixed engrams over classical, excitatory-only engrams. Towards this end, we consider large recurrent spiking networks with symmetrical Hebbian synaptic plasticity at both inhibitory-to-inhibitory (I-to-I) and inhibitoryto-excitatory (I-to-E) synapses. The conjunction of these rules can robustly stabilize embedded EI assemblies in the asynchronous irregular regime. Assemblies can then be reactivated by two distinct mechanisms: direct stimulation of the engram or disinhibition through the inhgram. Both mechanisms of recall lead to reliable pattern completion and separation. Crucially, we show that networks that lack I-to-I plasticity show weak recall and cannot discriminate between overlapping engrams via disinhibitory activation. This suggests that inhibitory plasticity can facilitate recall of overlapping engrams, with inhibitory neurons controlling multiple excitatory engrams. Furthermore, we show that inhgrams can emerge from pre-existing E-I-E loops in the network’s random connectivity. Our work proposes that inhibitory plasticity is a plausible mechanism for high-quality disinhibitory recall, allowing inhibitory neurons to selectively control multiple excitatory engrams through synapse-specific plasticity rules. AUTHOR SUMMARY The brain is thought to store memories in the form of engrams, groups of neurons that reactivate together during memory recall. Until recently, research focused almost exclusively on excitatory neurons as the building blocks of these memory traces, while inhibitory neurons were assumed to play a supporting role, responsible only for keeping network activity stable. However, recent experimental work has challenged this notion by showing that inhibitory neurons appear to form their own memory-related assemblies (inhgrams). In fact, manipulating inhibition in humans and animals can unmask or erase memories. This raises a fundamental question: what synaptic mechanisms could support such excitatory-inhibitory memory assemblies, and how would the brain use them to retrieve memories? Here, we used simulations of large spiking networks of excitatory and inhibitory neurons to show that when inhibitory synapses undergo plasticity, memories can be selectively retrieved by silencing inhibitory neurons, even when multiple memories partially overlap. Moreover, inhibitory plasticity amplifies pre-existing connectivity motifs, making the inhibitory component of a memory predictable before it is even formed. Our results suggest that inhibitory neurons are active organizers of memory retrieval, not just stabilizers, and play an important role in learning how to discriminate between similar memories.