Interplay of Intrinsic and Synaptic Conductances in the Generation of High-Frequency Oscillations in Interneuronal Networks with Irregular Spiking

Abstract

High-frequency oscillations (above 30 Hz) have been observed in sensory and higher-order brain areas, and are believed to constitute a general hallmark of functional neuronal activation. Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations. Certain classes of interneurons exhibit subthreshold oscillations, but the effect of this intrinsic neuronal property on the population rhythm is not completely understood. We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations, and elucidate the dynamical mechanisms that underlie this phenomenon. We simulate neuronal networks composed of either Integrate-and-Fire (IF) or Generalized Integrate-and-Fire (GIF) neurons. The IF model displays purely passive subthreshold dynamics, while the GIF model exhibits subthreshold damped oscillations. Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment, and fire irregularly at a lower rate than population frequency. We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i) the firing rate response to the noisy background input, ii) the membrane potential distribution, and iii) the shape of Inhibitory Post-Synaptic Potentials (IPSPs). For hyperpolarizing inhibition, the GIF IPSP profile (factor iii)) exhibits post-inhibitory rebound, which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations. This effect dominates the network dynamics, hence GIF networks display stronger oscillations than IF networks. However, the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution (factors i) and ii), respectively), which tend to decrease synchrony. If inhibition is shunting instead of hyperpolarizing, post-inhibitory rebound is not elicited and factors i) and ii) dominate, yielding lower synchrony in GIF networks than in IF networks.

Critical Slowing Down Governs the Transition to Neuron Spiking

“…3 b, c ). It has been noted that the membrane near the bifurcation behaves as an underdamped RLC circuit [ 40 ]. We derived the recovery rate by fitting the 500 sampling points interval after each perturbation of size σ 3 and variance and autocorrelation from the 5000 sample point segment preceding each perturbation.…”

The rat suprachiasmatic nucleus: the master clock ticks at 30 Hz

“…In networks of neurons receiving tonic excitatory input, mutual coupling by inhibitory synapses can lead to synchronous high frequency oscillations that arise from subthreshold oscillations of membrane potential; these enhance synchrony by introducing a depolarization that is mediated by a post‐inhibitory rebound, and this is correlated among neurons due to common inhibitory input. In network models, this can give rise to harmonic ISI distributions similar to those reported in the present study (Baroni et al ., ). Because the primary retinal recipient neurons in the SCN are all GABAergic and subject to an input that is predominantly excitatory, if they are mutually interconnected, then conditions appear to be ripe for synchronization of high frequency oscillatory activity.…”

NCAM Regulates Inhibition and Excitability in Layer 2/3 Pyramidal Cells of Anterior Cingulate Cortex

“…Modeling studies indicate that the generation of gamma oscillations depends on the strength and timing of inhibition in the network (Economo and White, 2012; Kuki et al, 2015; Tikidji-Hamburyan et al, 2015), the presence of asynchronous release from inhibitory neurons (Volman et al, 2011), as well as the excitability of both excitatory and inhibitory cells (Baroni et al, 2014). Changes in any of these factors can affect the period of oscillations, as well as the duration of oscillatory episodes.…”