[1]陆言,龚晓亮,谢非,等.基于复杂网络的秀丽隐杆线虫神经系统性质研究进展[J].中国医学物理学杂志,2022,39(11):1431-1440.[doi:DOI:10.3969/j.issn.1005-202X.2022.11.018]
　LU Yan,GONG Xiaoliang,XIE Fei,et al.Advances in research of properties of the neural system in Caenorhabditis elegans based on complex network[J].Chinese Journal of Medical Physics,2022,39(11):1431-1440.[doi:DOI:10.3969/j.issn.1005-202X.2022.11.018]
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基于复杂网络的秀丽隐杆线虫神经系统性质研究进展()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
39卷
期数:
2022年第11期
页码:
1431-1440
栏目:
其他（激光医学等）
出版日期:
2022-11-25

文章信息/Info

Title:
Advances in research of properties of the neural system in Caenorhabditis elegans based on complex network
文章编号:
1005-202X（2022）11-1431-10
作者:
陆言; 龚晓亮; 谢非; 钱晖; 庞路; 吴统琦
同济大学电子与信息工程学院， 上海 200092
Author(s):
LU Yan;  GONG Xiaoliang;  XIE Fei;  QIAN Hui;  PANG Lu;  WU Tongqi
School of Electronic and Information Engineering, Tongji University, Shanghai 200092, China
关键词:
秀丽隐杆线虫; 生物神经网络; 复杂网络; 连接组; 信息论
Keywords:
Caenorhabditis elegans biological neural network complex network connectome information theory
分类号:
R318；TP273
DOI:
DOI:10.3969/j.issn.1005-202X.2022.11.018
文献标志码:
A
摘要:
秀丽隐杆线虫具有结构简单、易于开展实验、组成与人类神经系统类似的特点，在复杂神经功能与神经系统疾病相关研究中具有重要地位，因而成为了第一个被完全测定连接组，即全体神经连接的生物。本研究关注以复杂网络为出发点的秀丽隐杆线虫神经网络的研究工作，归纳总结了该领域的研究进展。介绍了秀丽隐杆线虫的研究背景，并从静态、时变、动力学这3种研究性质出发，分别进行概述与分析讨论，并说明了相关研究成果的实际应用情况，最后探讨了线虫神经系统性质研究方面可能存在的问题，为下一步研究提供思路。
Abstract:
Abstract: Caenorhabditis elegans (C.elegans) with simple structures, easiness of being experimented with and a similar formation to human neural system plays an important role in researches on complex neural functions and nervous system associated diseases, and thus becomes the first biological specie which has a completed and comprehensive map of neural connections. The study focuses on the recent researches of C.elegans neural network based on complex network, and summarizes its research advances. After introducing C.elegans research background, the properties of the neural system in C.elegans are overviewed and analyzed from the aspects of static, time-varying and dynamic properties, and then the practical applications of the obtained research results are reviewed. Finally, several potential problems existing in the study of the nervous system in C.elegans are discussed, thereby providing some ideas for the further research.

相似文献/References:

[1]任婧雯,董朝轶,朱美佳,等.基于条件互信息的动态贝叶斯法探明生物神经元网络连接结构[J].中国医学物理学杂志,2021,38(6):773.[doi:DOI:10.3969/j.issn.1005-202X.2021.06.021]
　REN Jingwen,DONG Chaoyi,et al.Identification of biological neuron network connection structures by dynamic Bayesian network method based on conditional mutual information[J].Chinese Journal of Medical Physics,2021,38(11):773.[doi:DOI:10.3969/j.issn.1005-202X.2021.06.021]

备注/Memo

备注/Memo:
【收稿日期】2022-06-10 【基金项目】上海市国际合作项目（19490712800）；同济大学思政课题（4250107074/025）；同济大学实验教改项目（0800104294）；同济大学国创项目（0800107900） 【作者简介】陆言，研究方向：基于复杂网络方法的神经网络性质研究，E-mail: robinluaa@outlook.com 【通信作者】龚晓亮，博士，工程师，研究方向：脑与认知智能计算研究与教学，E-mail: gxllshsh@tongji.edu.cn
更新日期/Last Update: 2022-11-25