Network and cellular mechanisms underlying heterogeneous excitatory/inhibitory balanced states

Abstract

Recent work has explored spatiotemporal relationships between excitatory (E) and inhibitory (I) signaling within neural networks, and the effect of these relationships on network activity patterns. Data from these studies have indicated that excitation and inhibition are maintained at a similar level across long time periods and that excitatory and inhibitory currents may be tightly synchronized. Disruption of this balance—leading to an aberrant E/I ratio—is implicated in various brain pathologies. However, a thorough characterization of the relationship between E and I currents in experimental settings is largely impossible, due to their tight regulation at multiple cellular and network levels. Here, we use biophysical neural network models to investigate the emergence and properties of balanced states by heterogeneous mechanisms. Our results show that a network can homeostatically regulate the E/I ratio through interactions among multiple cellular and network factors, including average firing rates, synaptic weights and average neural depolarization levels in excitatory/inhibitory populations. Complex and competing interactions between firing rates and depolarization levels allow these factors to alternately dominate network dynamics in different synaptic weight regimes. This leads to the emergence of distinct mechanisms responsible for determining a balanced state and its dynamical correlate. Our analysis provides a comprehensive picture of how E/I ratio changes when manipulating specific network properties, and identifies the mechanisms regulating E/I balance. These results provide a framework to explain the diverse, and in some cases, contradictory experimental observations on the E/I state in different brain states and conditions.

Heterogeneous mechanisms for synchronization of networks of resonant neurons under different E/I balance regimes

“…These last two regimes are independent of neural resonance properties but only depend on structural network properties, coinciding with previous results observed in similar networks consisting of type 1 neurons (Wu et al, 2020).…”

“…The networks contained equal numbers of E and I cells so that the relative contributions of excitatory and inhibitory signaling in the network could be directly compared and controlled by the relative values of the synaptic strengths, w E and w I . In most brain networks, E cells outnumber I cells with a ratio of about 10:1, and we have previously shown that qualitatively similar E/I regulation occurs in networks with more physiologically accurate fractions of cell types (Wu, Aton et al, 2020). Additionally, the networks considered here had a fixed connectivity density (3%) that is within the range of reported estimates for local connectivity in hippocampal brain areas, but higher than the reported median (Tecuatl et al, 2021).…”

“…By systematically varying synaptic strength, the network E/I level forms a non-monotonic trajectory in the total current-vs-E/I ratio relationship. In previous work, we have shown that similar loop trajectories in the total currentvs-E/I ratio as excitatory synaptic strength is increased occur in networks consisting of model neurons with type 1 (i.e., integrator) excitability (Wu et al, 2020). In those networks, the qualitative shape of the trajectory loop did not depend on the ratio of E and I cells, the network connectivity density or the network connectivity topology.…”

The homeostatic homunculus: rethinking deprivation-triggered reorganisation

“…Here, we define brain homeostasis as the mechanisms that would either strengthen or weaken activity that is respectively above or below what is necessary to maintain baseline function and activity balance at either a local or network level. While homeostatic control of neuronal activity at the cellular level has been widely investigated in the last two decades [9,10], the study of biological mechanisms underlying homeostatic control of neural network function is receiving attention only more recently [11][12][13]. In this context, development, deprivation and activity-dependent plasticity constitute real challenges to maintaining balance within the sensorimotor system, without over-constraining plasticity that is vital for adaptive changes.…”

The role of the prefrontal cortex in social interactions of animal models and the implications for autism spectrum disorder

“…Multiple synaptic or circuit-level factors establish and tightly regulate neuronal E/I balance ( 163 ). The balance between excitatory and inhibitory synapses in the brain is maintained through a complex interplay of several factors.…”