Inhibitory Motifs Quench Synchrony Induced by Excitatory Motifs in Biological Neuronal Networks

Abstract

AO_SCPLOWBSTRACTC_SCPLOWThe connectivity in biological neuronal networks is known to deviate significantly from the random network (Erd[o]s-Renyi) model. Specifically, di-synaptic motifs like reciprocal, convergent, divergent, and chain are found to be either over-represented or under-represented in certain brain regions. Over-representation of such motifs among excitatory neurons is known to induce synchrony. However, cortical activity is typically asynchronous. Thus, it remains unclear how synchrony induced by excitatory motifs may be reduced to physiological levels. To address this question, we systematically vary the prevalence of these four motifs in an Excitatory-Inhibitory (EI) network. We found that over-representation of chain and convergent motifs in the excitatory population led to increased firing rates and greater synchrony. However, this excess synchrony was quenched when we introduced the same type of motifs among inhibitory neurons. Because of the overabundance of motifs, some inhibitory neurons received fewer recurrent inhibitory inputs. Such weakly coupled neurons were primarily driven by uncorrelated external inputs, and therefore, these neurons exerted stronger inhibition on excitatory neurons and reduced both synchrony and firing rates. Thus, we also provide a new mechanism by which synchrony can be controlled in excitatory-inhibitory networks. We predict that the same kind of di-synaptic motifs should be present in both excitatory and inhibitory neurons. Significance StatementComputational models predict that over-representation of di-synaptic motifs among excitatory neurons (as is experimentally observed) should lead to highly synchronous network activity. However, cortical activity is largely asynchronous. To reconcile this mismatch between structural connectivity and network activity we propose a novel mechanism to quench the synchrony. We show that motifs in the inhibitory population can quench the synchrony produced by excitatory motifs. We found that inhibitory neurons that received fewer inhibitory inputs are crucial for quenching the synchrony. Thus, we predict the existence of di-synaptic motifs among inhibitory neurons and argue that modulation of inhibitory neurons with less recurrent connectivity (e.g. SST+ neurons) have a more prominent role in controlling network activity state.