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峰频率适应有助于昆虫嗅觉投射神经元中输入梯度的编码。

Spike frequency adaptation facilitates the encoding of input gradient in insect olfactory projection neurons.

作者信息

Lee Hayeong, Kostal Lubomir, Kanzaki Ryohei, Kobayashi Ryota

机构信息

School of Engineering, The University of Tokyo, Tokyo, 113-8656, Japan.

Institute of Physiology, Czech Academy of Sciences, Prague, 142 20, Czech Republic.

出版信息

Biosystems. 2023 Jan;223:104802. doi: 10.1016/j.biosystems.2022.104802. Epub 2022 Nov 12.

Abstract

The olfactory system in insects has evolved to process the dynamic changes in the concentration of food odors or sex pheromones to localize the nutrients or conspecific mating partners. Experimental studies have suggested that projection neurons (PNs) in insects encode not only the stimulus intensity but also its rate-of-change (input gradient). In this study, we aim to develop a simple computational model for a PN to understand the mechanism underlying the coding of the rate-of-change information. We show that the spike frequency adaptation is a potential key mechanism for reproducing the phasic response pattern of the PN in Drosophila. We also demonstrate that this adaptation mechanism enables the PN to encode the rate-of-change of the input firing rate. Finally, our model predicts that the PN exhibits the intensity-invariant response for the pulse and ramp odor stimulus. These results suggest that the developed model is useful for investigating the coding principle underlying olfactory information processing in insects.

摘要

昆虫的嗅觉系统已经进化到能够处理食物气味或性信息素浓度的动态变化,以定位营养物质或同种交配伙伴。实验研究表明,昆虫中的投射神经元(PNs)不仅编码刺激强度,还编码其变化率(输入梯度)。在本研究中,我们旨在为PN开发一个简单的计算模型,以了解变化率信息编码背后的机制。我们表明,脉冲频率适应是在果蝇中重现PN的相位响应模式的潜在关键机制。我们还证明,这种适应机制使PN能够编码输入放电率的变化率。最后,我们的模型预测,PN对脉冲和斜坡气味刺激表现出强度不变的响应。这些结果表明,所开发的模型对于研究昆虫嗅觉信息处理的编码原理是有用的。

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