A Phase Model of Temperature-Dependent Mammalian Cold Receptors

Roper, Peter; Bressloff, Paul C.; Longtin, André

doi:10.1162/089976600300015510

Cited by 6 publications

(13 citation statements)

References 19 publications

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“…Spike bursts evoke higher levels of synaptic neurotransmitter compared to single spikes more sparsely distributed in time. Additionally, bursts might enable more precise information transfer compared to single spikes because spike burst patterns can drive higher neurons more efficiently (Roper et al, 2000;Krahe and Gabbiani, 2004). The central nervous system is able to discriminate between temporal spike train patterns, which have the same mean firing rate but correspond to different temperatures.…”

Section: Discussionmentioning

confidence: 99%

Neural Code for Ambient Heat Detection in Elaterid Beetles

Merivee

Must

Nurme

et al. 2020

Front. Behav. Neurosci.

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Environmental thermal conditions play a major role at all levels of biological organization; however, there is little information on noxious high temperature sensation crucial in behavioral thermoregulation and survival of small ectothermic animals such as insects. So far, a capability to unambiguously encode heat has been demonstrated only for the sensory triad of the spike bursting thermo-and two bimodal hygrothermoreceptor neurons located in the antennal dome-shaped sensilla (DSS) in a carabid beetle. We used extracellular single sensillum recording in the range of 20-45 • C to demonstrate that a similar sensory triad in the elaterid Agriotes obscurus also produces high temperature-induced bursty spike trains. Several parameters of the bursts are temperature dependent, allowing the neurons in a certain order to encode different, but partly overlapping ranges of heat up to lethal levels in a graded manner. ISI in a burst is the most useful parameter out of six. Our findings consider spike bursting as a general, fundamental quality of the classical sensory triad of antennal thermo-and hygro-thermoreceptor neurons widespread in many insect groups, being a flexible and reliable mode of coding unfavorably high temperatures. The possible involvement of spike bursting in behavioral thermoregulation of the beetles is discussed. By contrast, the mean firing rate of the neurons in regular and bursty spike trains combined does not carry useful thermal information at the high end of noxious heat.

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Section: Discussionmentioning

confidence: 99%

Neural Code for Ambient Heat Detection in Elaterid Beetles

Merivee

Must

Nurme

et al. 2020

Front. Behav. Neurosci.

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“…This model has seen increasing interest in recent years among theoreticians, primarily because the QIF neuron has the same properties as any type I neuron whenever the ring rate is low (Ermentrout & Kopell, 1986;Ermentrout, 1996). Among other studies, Roper, Bressloff, and Longtin (2000) studied the critical slowing down and stochastic resonance/trapping effects that occur close to the saddle-node bifurcation. QIF neurons have also been used in network studies: Latham, Richmond, Nelson, and Nirenberg (2000) studied the equilibrium properties of the background state of large networks, and Mato (2001, 2003) studied the synchronization properties of networks of QIF neurons in the absence of noise.…”

Section: Discussionmentioning

confidence: 99%

Firing Rate of the Noisy Quadratic Integrate-and-Fire Neuron

2003

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We calculate the ring rate of the quadratic integrate-and-re neuron in response to a colored noise input current. Such an input current is a good approximation to the noise due to the random bombardment of spikes, with the correlation time of the noise corresponding to the decay time of the synapses. The key parameter that determines the ring rate is the ratio of the correlation time of the colored noise, ¿ s , to the neuronal time constant, ¿ m . We calculate the ring rate exactly in two limits: when the ratio, ¿ s =¿ m , goes to zero (white noise) and when it goes to in nity. The correction to the short correlation time limit is O.¿ s =¿ m /, which is qualitatively different from that of the leaky integrate-and-re neuron, where the correction is O.The difference is due to the different boundary conditions of the probability density function of the membrane potential of the neuron at ring threshold. The correction to the long correlation time limit is O.¿ m =¿ s /. By combining the short and long correlation time limits, we derive an expression that provides a good approximation to the ring rate over the whole range of ¿ s =¿ m in the suprathreshold regimethat is, in a regime in which the average current is suf cient to make the cell re. In the subthreshold regime, the expression breaks down somewhat when ¿ s becomes large compared to ¿ m .

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“…Apart from those conductance-based models, a fully ionic model has been proposed by Longtin and Hinzer [ 5 ], which discussed the stochastic action potential phase model specifically for a cat's lingual cold receptor. This model was further simplified by Roper et al [ 14 ], namely, by introducing a simplified phase differential equation. It was demonstrated that the corresponding model was able to approximate the Longtin-Hinzer model for temperature interval 17.8°C to 40°C.…”

Section: Introductionmentioning

confidence: 99%

“…It was demonstrated that the corresponding model was able to approximate the Longtin-Hinzer model for temperature interval 17.8°C to 40°C. Compared to the conductance-based model, Roper's model [ 14 ] offered a relatively simple mathematical description. However, we discovered that this model did not lead to a realistic description on phenomena that occurred in higher or lower temperature conditions.…”

Section: Introductionmentioning

confidence: 99%

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A Coupled Phase-Temperature Model for Dynamics of Transient Neuronal Signal in Mammals Cold Receptor

Kirana

Alatas

Irzaman

2016

Journal of Biophysics

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We propose a theoretical model consisting of coupled differential equation of membrane potential phase and temperature for describing the neuronal signal in mammals cold receptor. Based on the results from previous work by Roper et al., we modified a nonstochastic phase model for cold receptor neuronal signaling dynamics in mammals. We introduce a new set of temperature adjusted functional parameters which allow saturation characteristic at high and low steady temperatures. The modified model also accommodates the transient neuronal signaling process from high to low temperature by introducing a nonlinear differential equation for the “effective temperature” changes which is coupled to the phase differential equation. This simple model can be considered as a candidate for describing qualitatively the physical mechanism of the corresponding transient process.

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A Phase Model of Temperature-Dependent Mammalian Cold Receptors

Cited by 6 publications

References 19 publications

Neural Code for Ambient Heat Detection in Elaterid Beetles

Neural Code for Ambient Heat Detection in Elaterid Beetles

Firing Rate of the Noisy Quadratic Integrate-and-Fire Neuron

A Coupled Phase-Temperature Model for Dynamics of Transient Neuronal Signal in Mammals Cold Receptor

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