Competing Mechanisms of Gamma and Beta Oscillations in the Olfactory Bulb Based on Multimodal Inhibition of Mitral Cells Over a Respiratory Cycle

David, François; Courtiol, Emmanuelle; Buonviso, Nathalie; Fourcaud-Trocmé, Nicolas

doi:10.1523/eneuro.0018-15.2015

Cited by 48 publications

(62 citation statements)

References 131 publications

(247 reference statements)

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“…; David et al . ), contributed to fast oscillatory synchrony in our bulb slices. Our mouse and rat bulb slices generally also included portions of the anterior olfactory nucleus and piriform cortex, leaving open the possibility that OSN stimulation in our experiments could have excited cortical cells that provide feedback.…”

Section: Resultsmentioning

confidence: 74%

“…Finally, we wondered whether excitatory feedback from the olfactory cortex, which can impact the frequency of bulbar oscillations (Martin et al 2004;Lowry & Kay, 2007;Fourcaud-Trocmé et al 2011;Boyd et al 2012;David et al 2015), contributed to fast oscillatory synchrony in our bulb slices. Our mouse and rat bulb slices generally also included portions of the anterior olfactory nucleus and piriform cortex, leaving open the possibility that OSN stimulation in our experiments could have excited cortical cells that provide feedback.…”

Section: Cortical Feedback Does Not Contribute To Synchronized Activimentioning

confidence: 99%

“…Excitatory connections amongst the pool of glutamatergic cells may also facilitate the oscillations generated by such feedback loops in some circuits (Fisahn et al 1998;Traub et al 2004). Besides gamma oscillations, many brain circuits engage in somewhat slower beta oscillations that may rely on similar interactions between excitatory and inhibitory cells (Kopell et al 2000;Whittington et al 2000;David et al 2015;Kay, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Intraglomerular gap junctions enhance interglomerular synchrony in a sparsely connected olfactory bulb network

Pouille

McTavish

Hunter

et al. 2017

The Journal of Physiology

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Key pointsr Despite sparse connectivity, population-level interactions between mitral cells (MCs) and granule cells (GCs) can generate synchronized oscillations in the rodent olfactory bulb.r Intraglomerular gap junctions between MCs at the same glomerulus can greatly enhance synchronized activity of MCs at different glomeruli.r The facilitating effect of intraglomerular gap junctions on interglomerular synchrony is through triggering of mutually synchronizing interactions between MCs and GCs.r Divergent connections between MCs and GCs make minimal direct contribution to synchronous activity.Abstract A dominant feature of the olfactory bulb response to odour is fast synchronized oscillations at beta (15-40 Hz) or gamma (40-90 Hz) frequencies, thought to be involved in integration of olfactory signals. Mechanistically, the bulb presents an interesting case study for understanding how beta/gamma oscillations arise. Fast oscillatory synchrony in the activity of output mitral cells (MCs) appears to result from interactions with GABAergic granule cells (GCs), yet the incidence of MC-GC connections is very low, around 4%. Here, we combined computational and experimental approaches to examine how oscillatory synchrony can nevertheless arise, focusing mainly on activity between 'non-sister' MCs affiliated with different glomeruli (interglomerular synchrony). In a sparsely connected model of MCs and GCs, we found first that interglomerular synchrony was generally quite low, but could be increased by a factor of 4 by physiological levels of gap junctional coupling between sister MCs at the same glomerulus. This effect was due to enhanced mutually synchronizing interactions between MC and GC populations. The potent role of gap junctions was confirmed in patch-clamp recordings in bulb slices from wild-type and connexin 36-knockout (KO) mice. KO reduced both beta and gamma local field potential oscillations as well as synchrony of inhibitory signals in pairs of non-sister MCs. These effects were independent of potential KO actions on network excitation. Divergent synaptic connections did not contribute directly to the vast majority of synchronized signals. Thus, in a sparsely connected network, gap junctions between a small subset of cells can, through population effects, greatly amplify oscillatory synchrony amongst unconnected cells.

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Section: Resultsmentioning

confidence: 74%

Section: Cortical Feedback Does Not Contribute To Synchronized Activimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Intraglomerular gap junctions enhance interglomerular synchrony in a sparsely connected olfactory bulb network

Pouille

McTavish

Hunter

et al. 2017

The Journal of Physiology

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show abstract

“…The other relies on transitions from nonspiking to spiking states, which gives strong pulses of inhibition to mitral cells (David et al, 2015).…”

Section: What the Oscillations Representmentioning

confidence: 99%

Gamma and Beta Oscillations Define a Sequence of Neurocognitive Modes Present in Odor Processing

Frederick

Brown

Brim

et al. 2016

Journal of Neuroscience

102

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Olfactory system beta (15-35 Hz) and gamma (40 -110 Hz) oscillations of the local field potential in mammals have both been linked to odor learning and discrimination. Gamma oscillations represent the activity of a local network within the olfactory bulb, and beta oscillations represent engagement of a systemwide network. Here, we test whether beta and gamma oscillations represent different cognitive modes using the different demands of go/no-go and two-alternative choice tasks that previously were suggested to favor beta or gamma oscillations, respectively. We reconcile previous studies and show that both beta and gamma oscillations occur in both tasks, with gamma dominating the early odor sampling period (2-4 sniffs) and beta dominating later. The relative power and coherence of both oscillations depend separately on multiple factors within both tasks without categorical differences across tasks. While the early/gammaassociated period occurs in all trials, rats can perform above chance without the later/beta-associated period. Longer sampling, which includes beta oscillations, is associated with better performance. Gamma followed by beta oscillations therefore represents a sequence of cognitive and neural states during odor discrimination, which can be separately modified depending on the demands of a task and odor discrimination. Additionally, fast (85 Hz) and slow (70 Hz) olfactory bulb gamma oscillation sub-bands have been hypothesized to represent tufted and mitral cell networks, respectively (Manabe and Mori, 2013). We find that fast gamma favors the early and slow gamma the later (beta-dominated) odor-sampling period and that the relative contributions of these oscillations are consistent across tasks.

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“…Indeed, synaptic inhibition in this deep layer is likely to affect the timing, rather than the existence, of principal neuron action potentials (discussed in [8]; [26]), suggesting a common clock for coordinating the spiking activity exported to other regions of the brain. These gamma oscillations transition to a lower (beta) frequency during bidirectional interactions with piriform cortex [27, 28], and are embedded within theta-band oscillations that can be directly driven by respiration but may also be supported by the intrinsic theta-band rhythmicity of ET cells [29]. Notably, ET cells may be the primary source of mitral cell excitation; mounting evidence indicates that ET cell neurites are interposed between afferent fibers and mitral cell dendrites, as well as interacting with other juxtaglomerular interneurons in the glomerular layer network [12, 30-32].…”

Section: Model Conceptionmentioning

confidence: 99%

Generative Biophysical Modeling of Dynamical Networks in the Olfactory System

Cleland

2018

Methods in Molecular Biology

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Generative models are computational models designed to generate appropriate values for all of their embedded variables, thereby simulating the response properties of a complex system based on the coordinated interactions of a multitude of physical mechanisms. In systems neuroscience, generative models are generally biophysically based compartmental models of neurons and networks that are explicitly multiscale, being constrained by experimental data at multiple levels of organization from cellular membrane properties to large-scale network dynamics. As such, they are able to explain the origins of emergent properties in complex systems, and serve as tests of sufficiency and as quantitative instantiations of working hypotheses that may be too complex to simply intuit. Moreover, when adequately constrained, generative biophysical models are able to predict novel experimental outcomes, and consequently are powerful tools for experimental design. We here outline a general strategy for the iterative design and implementation of generative, multiscale biophysical models of neural systems. We illustrate this process using our ongoing, iteratively developing model of the mammalian olfactory bulb. Because the olfactory bulb exhibits diverse and interesting properties at multiple scales of organization, it is an attractive system in which to illustrate the value of generative modeling across scales.

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Competing Mechanisms of Gamma and Beta Oscillations in the Olfactory Bulb Based on Multimodal Inhibition of Mitral Cells Over a Respiratory Cycle

Abstract: Visual Abstract

Cited by 48 publications

References 131 publications

Intraglomerular gap junctions enhance interglomerular synchrony in a sparsely connected olfactory bulb network

Intraglomerular gap junctions enhance interglomerular synchrony in a sparsely connected olfactory bulb network

Gamma and Beta Oscillations Define a Sequence of Neurocognitive Modes Present in Odor Processing

Generative Biophysical Modeling of Dynamical Networks in the Olfactory System

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