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用于秀丽隐杆线虫趋化性的环境中化学梯度内部表示的计算模型。

A computational model of internal representations of chemical gradients in environments for chemotaxis of Caenorhabditis elegans.

机构信息

Department of System Cybernetics, Institute of Engineering, Hiroshima University, Higashi-Hiroshima, Hiroshima, Japan.

Department of System Cybernetics, Graduate School of Engineering, Hiroshima University, Higashi-Hiroshima, Hiroshima, Japan.

出版信息

Sci Rep. 2018 Nov 21;8(1):17190. doi: 10.1038/s41598-018-35157-1.

Abstract

The small roundworm Caenorhabditis elegans employs two strategies, termed pirouette and weathervane, which are closely related to the internal representation of chemical gradients parallel and perpendicular to the travelling direction, respectively, to perform chemotaxis. These gradients must be calculated from the chemical information obtained at a single point, because the sensory neurons are located close to each other at the nose tip. To formulate the relationship between this sensory input and internal representations of the chemical gradient, this study proposes a simple computational model derived from the directional decomposition of the chemical concentration at the nose tip that can generate internal representations of the chemical gradient. The ability of the computational model was verified by using a chemotaxis simulator that can simulate the body motions of pirouette and weathervane, which confirmed that the computational model enables the conversion of the sensory input and head-bending angles into both types of gradients with high correlations of approximately r > 0.90 (p < 0.01) with the true gradients. In addition, the chemotaxis index of the model was 0.64, which is slightly higher than that in the actual animal (0.57). In addition, simulation using a connectome-based neural network model confirmed that the proposed computational model is implementable in the actual network structure.

摘要

秀丽隐杆线虫采用了两种策略,分别称为旋转和风向标,它们分别与平行和垂直于运动方向的化学梯度的内部表示密切相关,以进行趋化性。这些梯度必须根据在单个点获得的化学信息进行计算,因为感觉神经元彼此靠近在鼻尖。为了制定这种感觉输入与化学梯度的内部表示之间的关系,本研究提出了一个简单的计算模型,该模型源自于鼻尖处化学浓度的方向分解,可以生成化学梯度的内部表示。通过使用能够模拟旋转和风向标身体运动的趋化性模拟器来验证计算模型的能力,这证实了计算模型能够将感觉输入和头部弯曲角度转换为两种类型的梯度,其相关性约为 r>0.90(p<0.01)与真实梯度。此外,模型的趋化指数为 0.64,略高于实际动物(0.57)。此外,基于连接组的神经网络模型的模拟证实了所提出的计算模型在实际网络结构中是可实现的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec50/6249258/44081d7d3d92/41598_2018_35157_Fig1_HTML.jpg

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