scholarly journals Olfactory coding in the turbulent realm

2017 ◽  
Author(s):  
Vincent Jacob ◽  
Christelle Monsempès ◽  
Jean-Pierre Rospars ◽  
Jean-Baptiste Masson ◽  
Philippe Lucas
Keyword(s):  
White Noise ◽  
Firing Rate ◽  
Olfactory Receptor ◽  
Olfactory System ◽  
Time Course ◽  
Temporal Structure ◽  
Olfactory Receptor Neurons ◽  
Odor Source ◽  
Long Distance ◽  
Receptor Neurons

AbstractLong-distance olfactory search behaviors depend on odor detection dynamics. Due to turbulence, olfactory signals travel as bursts of variable concentration and spacing and are characterized by long-tail distributions of odor/no-odor events, challenging the computing capacities of olfactory systems. How animals encode complex olfactory scenes to track the plume far from the source remains unclear. Here we focus on the coding of the plume temporal dynamics in moths. We compare responses of olfactory receptor neurons (ORNs) and antennal lobe projection neurons (PNs) to sequences of pheromone stimuli either with white-noise patterns or with realistic turbulent temporal structures simulating a large range of distances (8 to 64 m) from the odor source. For the first time, we analyze what information is extracted by the olfactory system at large distances from the source. Neuronal responses are analyzed using linear–nonlinear models fitted with white-noise stimuli and used for predicting responses to turbulent stimuli. We found that neuronal firing rate is less correlated with the dynamic odor time course when distance to the source increases because of improper coding during long odor and no-odor events that characterize large distances. Rapid adaptation during long puffs does not preclude however the detection of puff transitions in PNs. Individual PNs but not individual ORNs encode the onset and offset of odor puffs for any temporal structure of stimuli. A higher spontaneous firing rate coupled to an inhibition phase at the end of PN responses contributes to this coding property. This allows PNs to decode the temporal structure of the odor plume at any distance to the source, an essential piece of information moths can use in their tracking behavior.Author SummaryLong-distance olfactory search is a difficult task because atmospheric turbulence erases global gradients and makes the plume discontinuous. The dynamics of odor detections is the sole information about the position of the source. Male moths successfully track female pheromone plumes at large distances. Here we show that the moth olfactory system encodes olfactory scenes simulating variable distances from the odor source by characterizing puff onsets and offsets. A single projection neuron is sufficient to provide an accurate representation of the dynamic pheromone time course at any distance to the source while this information seems to be encoded at the population level in olfactory receptor neurons.

scholarly journals Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth

2019 ◽  
Vol 16 (157) ◽  
pp. 20190246 ◽  
Author(s):  
Marie Levakova ◽  
Lubomir Kostal ◽  
Christelle Monsempès ◽  
Philippe Lucas ◽  
Ryota Kobayashi
Keyword(s):  
Olfactory Receptor ◽  
Time Course ◽  
Olfactory Receptor Neuron ◽  
Receptor Activation ◽  
Olfactory Receptor Neurons ◽  
Response Dynamics ◽  
Spike Threshold ◽  
Olfactory Stimuli ◽  
Receptor Neurons ◽  
The Brain

In order to understand how olfactory stimuli are encoded and processed in the brain, it is important to build a computational model for olfactory receptor neurons (ORNs). Here, we present a simple and reliable mathematical model of a moth ORN generating spikes. The model incorporates a simplified description of the chemical kinetics leading to olfactory receptor activation and action potential generation. We show that an adaptive spike threshold regulated by prior spike history is an effective mechanism for reproducing the typical phasic–tonic time course of ORN responses. Our model reproduces the response dynamics of individual neurons to a fluctuating stimulus that approximates odorant fluctuations in nature. The parameters of the spike threshold are essential for reproducing the response heterogeneity in ORNs. The model provides a valuable tool for efficient simulations of olfactory circuits.

scholarly journals Concentration-Invariant Odor Representation in the Olfactory System by Presynaptic Inhibition

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Danke Zhang ◽  
Yuanqing Li ◽  
Si Wu
Keyword(s):  
Olfactory Receptor ◽  
Olfactory System ◽  
Olfactory Receptor Neurons ◽  
Projection Neurons ◽  
Invariant Representation ◽  
Odor Concentration ◽  
Presynaptic Site ◽  
Divisive Normalization ◽  
Receptor Neurons ◽  
Parameter Condition

The present study investigates a network model for implementing concentration-invariant representation for odors in the olfactory system. The network consists of olfactory receptor neurons, projection neurons, and inhibitory local neurons. Receptor neurons send excitatory inputs to projection neurons, which are modulated by the inhibitory inputs from local neurons. The modulation occurs at the presynaptic site from a receptor neuron to a projection one, leading to the operation of divisive normalization. The responses of local interneurons are determined by the total activities of olfactory receptor neurons. We find that with a proper parameter condition, the responses of projection neurons become effectively independent of the odor concentration. Simulation results confirm our theoretical analysis.

scholarly journals Calcium-activated chloride channels clamp odor-evoked spike activity in olfactory receptor neurons

2018 ◽  
Author(s):  
Joseph D. Zak ◽  
Julien Grimaud ◽  
Rong-Chang Li ◽  
Chih-Chun Lin ◽  
Venkatesh N. Murthy
Keyword(s):  
Olfactory Receptor ◽  
Chloride Channels ◽  
Feedback Mechanism ◽  
Olfactory Receptor Neurons ◽  
Odor Source ◽  
Wild Type ◽  
Behavioral Deficits ◽  
Receptor Neurons

AbstractThe calcium-activated chloride channel anoctamin-2 (Ano2) is thought to amplify transduction currents in ORNs, a hypothesis supported by previous studies in dissociated neurons from Ano2-/- mice. Paradoxically, despite a reduction in transduction currents in Ano2-/- ORNs, their spike output for odor stimuli may be higher. We examined the role of Ano2 in ORNs in their native environment in freely breathing mice by imaging activity in ORN axons as they arrive in the olfactory bulb glomeruli. Odor-evoked responses in ORN axons of Ano2-/- mice were consistently larger for a variety of odorants and concentrations. In an open arena, Ano2-/- mice took longer to approach a localized odor source than wild-type mice, revealing clear olfactory behavioral deficits. Our studies provide the first in vivo evidence toward an alternative role for Ano2 in the olfactory transduction cascade, where it may serve as a feedback mechanism to clamp ORN spike output.

scholarly journals Cyclic-nucleotide–gated cation current and Ca2+-activated Cl current elicited by odorant in vertebrate olfactory receptor neurons

2016 ◽  
Vol 113 (40) ◽  
pp. 11078-11087 ◽  
Author(s):  
Rong-Chang Li ◽  
Yair Ben-Chaim ◽  
King-Wai Yau ◽  
Chih-Chun Lin
Keyword(s):  
Cyclic Nucleotide ◽  
Olfactory Receptor ◽  
Signal Amplification ◽  
Time Course ◽  
Olfactory Receptor Neurons ◽  
Cation Current ◽  
Nonselective Cation Channels ◽  
Predominant Component ◽  
Receptor Neurons ◽  
The Brain

Olfactory transduction in vertebrate olfactory receptor neurons (ORNs) involves primarily a cAMP-signaling cascade that leads to the opening of cyclic-nucleotide–gated (CNG), nonselective cation channels. The consequent Ca2+ influx triggers adaptation but also signal amplification, the latter by opening a Ca2+-activated Cl channel (ANO2) to elicit, unusually, an inward Cl current. Hence the olfactory response has inward CNG and Cl components that are in rapid succession and not easily separable. We report here success in quantitatively separating these two currents with respect to amplitude and time course over a broad range of odorant strengths. Importantly, we found that the Cl current is the predominant component throughout the olfactory dose–response relation, down to the threshold of signaling to the brain. This observation is very surprising given a recent report by others that the olfactory-signal amplification effected by the Ca2+-activated Cl current does not influence the behavioral olfactory threshold in mice.

scholarly journals Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in insects

2020 ◽  
Author(s):  
Mario Pannunzi ◽  
Thomas Nowotny
Keyword(s):  
Lateral Inhibition ◽  
Olfactory Receptor ◽  
Olfactory System ◽  
Antennal Lobe ◽  
Olfactory Receptor Neurons ◽  
Inhibition Mechanism ◽  
Alternative Mechanism ◽  
Odor Processing ◽  
Synaptic Interactions ◽  
Receptor Neurons

AbstractWhen flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, flies must solve several tasks, including reliably identifying mixtures of odorants and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these two tasks. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic (“ephaptic”) interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla. For both tasks, NSIs improve the insect olfactory system and outperform the standard lateral inhibition mechanism in the antennal lobe. These results shed light, from an evolutionary perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Odorants Suppress a Voltage-Activated K+ Conductance in Rat Olfactory Neurons

1999 ◽  
Vol 82 (1) ◽  
pp. 226-236 ◽  
Author(s):  
Fritz W. Lischka ◽  
John H. Teeter ◽  
Diego Restrepo
Keyword(s):  
Signal Transduction ◽  
Olfactory Receptor ◽  
Time Course ◽  
Olfactory Receptor Neurons ◽  
Delayed Rectifier ◽  
Ion Permeation ◽  
Olfactory Neurons ◽  
Receptor Neurons ◽  
Stimulation Of ◽  
Ion Conductances

Stimulation of olfactory receptor neurons (ORNs) with odors elicits an increase in the concentration of cAMP leading to opening of cyclic nucleotide-gated (CNG) channels and subsequent depolarization. Although opening of CNG channels is thought to be the main mechanism mediating signal transduction, modulation of other ion conductances by odorants has been postulated. To determine whether K+ conductances are modulated by odorants in mammalian ORNs, we examined the response of rat ORNs to odors by recording membrane current under perforated-patch conditions. We find that rat ORNs display two predominant types of responses. Thirty percent of the cells responded to odorants with activation of a CNG conductance. In contrast, in 55% of the ORNs, stimulation with odorants inhibited a voltage-activated K+ conductance ( I Ko). In terms of pharmacology, ion permeation, outward rectification, and time course for inactivation, I Ko resembled a delayed rectifier K+ conductance. The effect of odorants on I Ko was specific (only certain odorants inhibited I Ko in each ORN) and concentration dependent, and there was a significant latency between arrival of odorants to the cell and the onset of suppression. These results indicate that indirect suppression of a K+ conductance ( I Ko) by odorants plays a role in signal transduction in mammalian ORNs.

scholarly journals What the fly’s nose tells the fly’s brain

2015 ◽  
Vol 112 (30) ◽  
pp. 9460-9465 ◽  
Author(s):  
Charles F. Stevens
Keyword(s):  
Olfactory Receptor ◽  
Olfactory System ◽  
Small Population ◽  
Olfactory Receptor Neurons ◽  
Small Subset ◽  
Second Stage ◽  
The Third ◽  
Third Stage ◽  
Three Layer Architecture ◽  
Receptor Neurons

The fly olfactory system has a three-layer architecture: The fly’s olfactory receptor neurons send odor information to the first layer (the encoder) where this information is formatted as combinatorial odor code, one which is maximally informative, with the most informative neurons firing fastest. This first layer then sends the encoded odor information to the second layer (decoder), which consists of about 2,000 neurons that receive the odor information and “break” the code. For each odor, the amplitude of the synaptic odor input to the 2,000 second-layer neurons is approximately normally distributed across the population, which means that only a very small fraction of neurons receive a large input. Each odor, however, activates its own population of large-input neurons and so a small subset of the 2,000 neurons serves as a unique tag for the odor. Strong inhibition prevents most of the second-stage neurons from firing spikes, and therefore spikes from only the small population of large-input neurons is relayed to the third stage. This selected population provides the third stage (the user) with an odor label that can be used to direct behavior based on what odor is present.

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