  Strong inhibitory input to neurons, which occurs in balanced states of neural
networks, increases synaptic current fluctuations. This has led to the
assumption that inhibition contributes to the high spike-firing irregularity
observed in vivo. We used single compartment neuronal models with
time-correlated (due to synaptic filtering) and state-dependent (due to
reversal potentials) input to demonstrate that inhibitory input acts to
decrease membrane potential fluctuations, a result that cannot be achieved with
simplified neural input models. To clarify the effects on spike-firing
regularity, we used models with different spike-firing adaptation mechanisms
and observed that the addition of inhibition increased firing regularity in
models with dynamic firing thresholds and decreased firing regularity if
spike-firing adaptation was implemented through ionic currents or not at all.
This novel fluctuation-stabilization mechanism provides a new perspective on
the importance of strong inhibitory inputs observed in balanced states of
neural networks and highlights the key roles of biologically plausible inputs
and specific adaptation mechanisms in neuronal modeling.
