Biophysical model for gamma rhythms in the olfactory bulb via subthreshold oscillations

Abstract

Gamma oscillations in the olfactory bulb can be produced as an interaction of subthreshold oscillations (STOs) in the mitral cells (MCs) with inhibitory granule cells (GCs). The mechanism does not require that the GCs spike, and we work in a regime in which the MCs fire at rates lower than the fast gamma rhythm they create. The frequency of the network is that of the STOs, allowing the gamma to be modulated in amplitude with only small changes in frequency. Gamma oscillations could also be obtained with spiking GCs, but only for GCs firing close to population rate. Our mechanism differs from the more standard description of the gamma oscillation, in which the the decay time of the inhibitory cells is critical to the frequency of the network.mitral cell ͉ granule cell ͉ graded inhibition G amma oscillations (40-100 Hz) are produced in the mammalian olfactory bulb (OB) and many other structures in the nervous system (1-3). In the neocortex and the hippocampus, gamma oscillations are believed to depend on fast-spiking interneurons, created either by the interaction of inhibitory cells alone or as an interaction of excitatory pyramidal cells and inhibitory interneurons, such as basket cells (4,5). It is generally accepted that interactions between excitatory mitral cells (MCs) and inhibitory granule cells (GCs) at the dendrodendritic reciprocal synapse support gamma oscillations in the OB, but the physiological mechanisms of these oscillations are not well understood. Many slice studies focus on regimes in which the axonless GCs spike. However, it has been suggested, by contrast, that gamma oscillations in the OB depend on the subtheshold oscillations (STOs) in MCs, the excitatory cells of the OB (6), and that spikes from the GCs, the inhibitory cells of the OB, may not play a major part in the gamma oscillation of the OB (ref. 7 and see also Discussion). It is not understood what differences these features might make in the mechanism of synchronization of the OB gamma rhythm.It is well known that a target population of cells can be synchronized by a common pulse of inhibition (5,8,9). The synchronization comes mainly from a shared suppression of firing until the inhibition has worn off sufficiently for the excitatory cells to fire. If the target cells are identical in drive, they will fire simultaneously; if they have somewhat different drives, they will fire with a small lag (5). With graded inhibition, it is less clear how the inhibition provides the synchronization: there is no clear decay time of inhibition, because the amplitude and time course of the inhibition is not stereotyped.Here, we show that the features of STOs and graded inhibition can work together to produce a mechanism for the synchronization of gamma. We are interested in the regime in which MCs, the excitatory cells of the OB, spike with a firing rate significantly below that of the population frequency, as seen experimentally (10). Unlike the classical excitation-inhibition of the pyramidal interneuron network gamma (PING), in which the decay t...

Nonlinear effects of noradrenergic modulation of olfactory bulb function in adult rodents

“…Modulatory inputs on mitral and granule cells can potentially affect the dynamics of neural activity as well as spike timing and degrees of synchronization. Levels of synchronization among bulbar outputs have been proposed to contribute to odor processing and learning experimentally (Beshel et al 2007;Brea et al 2009;Kay et al 2009;Nusser et al 2001). Modulatory inputs to granule and mitral cells can potentially regulate oscillatory dynamics of olfactory bulb processing and hence change the processing of odors, as proposed early on by Freeman and colleagues (Di Prisco and Freeman 1985;Gray et al 1986) and shown recently in slices of young rats by Schoppa and colleagues (Gire and Schoppa 2008;Pandipati et al 2010).…”

Effects of Neuromodulation on Excitatory–Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

“…These studies pay less attention to the role of intrinsic cellular properties or the impact of more varied network structures, as the conceptual PING mechanism assumes strong E-I and I-E inter-connectivity as well as strong I-I intra-connectivity and burst frequencies are presumed to be dictated by properties of synaptic currents. However, as our biological understanding of the brain rapidly accelerates, the immense diversity of neuron properties, particularly of inhibitory interneurons, and network connectivities among these interneuron populations (Brea et al 2009;Kopell et al 2010;Best et al 2007;Klausberger et al 2003;Buhl et al 1994;Beierlein et al 2000;Barthó et al 2004;Somogyi and Klausberger 2005;Klausberger and Somogyi 2008;Gonchar and Burkhalter 1997;Beierlein et al 2003;Gibson et al 1999;Deco and Thiele 2011;Hasselmo and Giocomo 2006;Hasselmo and Sarter 2011;Sarter et al 2005) motivates computational research to investigate and understand dynamics arising from the interaction of cellular properties and network connectivity structures.…”

“…Given the paramount effect cholinergic modulation has on intrinsic cellular properties and a neuron's tendency to exhibit synchrony, here we investigate its influence on the synchronous dynamics of networks of inter-connected excitatory and inhibitory neurons (E-I networks), as such networks are ubiquitous in the brain (Brea et al 2009;Kopell et al 2010;Best et al 2007). The interactions of excitatory and inhibitory neurons can generate oscillatory bursts of synchronous spiking of excitatory cells which underlie rhythmic electrical activity observed in electroencephalogram (EEG) recordings associated with different brain states and cognition (Cannon et al 2014;Whittington et al 1995).…”

A preliminary study into emergent behaviours in a lattice of interacting nonlinear resonators and oscillators

“…For example [1], biophysical models to explain the gamma band oscillation in the olfactory bulb based on coupled subthreshold oscillators have been shown to exhibit synchronisation and coherence effects when driven with correlated inputs. Similarly, in recent models of temporal coding [2], competition for coherence driven by increased phase velocity of neural units in cases of coherent input from the connected neurons leads to different perspectives on assembly formation in collections of coupled oscillator neurons.…”