Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth
Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth
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DOI：
10.1098/rsif.2019.0246
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发表时间：
2019-08
影响因子：
3.9
通讯作者：
Marie Levakova;Lubomir Kostal;C. Monsempès;P. Lucas;R. Kobayashi
中科院分区：
文献类型：
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作者：
Marie Levakova;Lubomir Kostal;C. Monsempès;P. Lucas;R. Kobayashi
为了了解嗅觉刺激是如何在大脑中编码和处理的，建立嗅觉受体神经元的计算模型是很重要的。在这里，我们提出了一个简单可靠的蛾子ORN产生尖峰的数学模型。该模型包含了导致嗅觉受体激活和动作电位产生的化学动力学的简化描述。我们发现，由先前的峰值历史调节的自适应峰值阈值是一个有效的机制，可以再现ORN反应的典型相位-张力时间过程。我们的模型再现了单个神经元对波动刺激的反应动力学，近似于自然界中气味的波动。尖峰阈值的参数对于再现orn中的响应异质性至关重要。该模型为有效地模拟嗅觉回路提供了一个有价值的工具。
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.