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一种巨纤维系统逃避反应潜伏期的计算模型。

A Computational Model of the Escape Response Latency in the Giant Fiber System of .

机构信息

Institute of Healthy Ageing, and GEE, University College London, London WC1E 6BT, United Kingdom.

Max Planck Institute for Biology of Ageing, Cologne D-50931, Germany.

出版信息

eNeuro. 2019 Apr 15;6(2). doi: 10.1523/ENEURO.0423-18.2019. eCollection 2019 Mar-Apr.

DOI:10.1523/ENEURO.0423-18.2019
PMID:31001574
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6469880/
Abstract

The giant fiber system (GFS) is a multi-component neuronal pathway mediating rapid escape response in the adult fruit-fly , usually in the face of a threatening visual stimulus. Two branches of the circuit promote the response by stimulating an escape jump followed by flight initiation. A recent work demonstrated an age-associated decline in the speed of signal propagation through the circuit, measured as the stimulus-to-muscle depolarization response latency. The decline is likely due to the diminishing number of inter-neuronal gap junctions in the GFS of ageing flies. In this work, we presented a realistic conductance-based, computational model of the GFS that recapitulates the experimental results and identifies some of the critical anatomical and physiological components governing the circuit's response latency. According to our model, anatomical properties of the GFS neurons have a stronger impact on the transmission than neuronal membrane conductance densities. The model provides testable predictions for the effect of experimental interventions on the circuit's performance in young and ageing flies.

摘要

巨纤维系统(GFS)是一种多成分神经元通路,可介导成年果蝇的快速逃避反应,通常是面对威胁性的视觉刺激。该回路的两个分支通过刺激逃避跳跃,随后引发飞行启动来促进反应。最近的一项研究表明,随着年龄的增长,信号通过回路的传播速度会下降,其测量指标为刺激到肌肉去极化的反应潜伏期。这种下降可能是由于衰老果蝇 GFS 中神经元间隙连接数量的减少所致。在这项工作中,我们提出了一个现实的基于电导的 GFS 计算模型,该模型重现了实验结果,并确定了一些控制回路反应潜伏期的关键解剖学和生理学组成部分。根据我们的模型,GFS 神经元的解剖学特性对传输的影响比神经元膜电导密度更强。该模型为实验干预对年轻和衰老果蝇回路性能的影响提供了可测试的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/384c58080f4d/enu0021929130005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/b4900a2dc887/enu0021929130001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/474c203a1953/enu0021929130002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/32ac4554ac6c/enu0021929130003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/d78ce9bb0520/enu0021929130004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/384c58080f4d/enu0021929130005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/b4900a2dc887/enu0021929130001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/474c203a1953/enu0021929130002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/32ac4554ac6c/enu0021929130003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/d78ce9bb0520/enu0021929130004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/6469880/384c58080f4d/enu0021929130005.jpg

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