[1]徐龙春,张敏风,张岗,等.虚拟数字脑软件平台的研究与开发[J].中国医学物理学杂志,2019,36(12):1434-1439.[doi:DOI:10.3969/j.issn.1005-202X.2019.12.013]
　XU Longchun,ZHANG Minfeng,ZHANG Gang,et al.Research and development of virtual digital brain software package[J].Chinese Journal of Medical Physics,2019,36(12):1434-1439.[doi:DOI:10.3969/j.issn.1005-202X.2019.12.013]
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虚拟数字脑软件平台的研究与开发()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
36卷
期数:
2019年第12期
页码:
1434-1439
栏目:
医学影像物理
出版日期:
2019-12-25

文章信息/Info

Title:
Research and development of virtual digital brain software package
文章编号:
1005-202X（2019）12-1434-06
作者:
徐龙春1; 张敏风1; 张岗2; 邹越2; 赵文波2; 何乐民3; 周慧晶3; 颜淑敏3; 张光玉3
1.山东第一医科大学（山东省医学科学院）第二附属医院医学影像科， 山东 泰安 271000； 2.山东第一医科大学（山东省医学科学院）第二附属医院耳鼻咽喉科， 山东 泰安 271000； 3.山东第一医科大学（山东省医学科学院）放射学院， 山东 泰安 271016
Author(s):
XU Longchun1;  ZHANG Minfeng1;  ZHANG Gang2;  ZOU Yue2;  ZHAO Wenbo2;  HE Lemin3;  ZHOU Huijing3;  YAN Shumin3;  ZHANG Guangyu3
1. Department of Medical Imaging, the Second Affiliated Hospital of Shandong First Medical University (Shandong Academy of Medical Sciences), Tai’an 271000, China; 2. Department of Otorhinolaryngology, the Second Affiliated Hospital of Shandong First Medical University (Shandong Academy of Medical Sciences), Tai’an 271000, China; 3. Department of Radiology, Shandong First Medical University (Shandong Academy of Medical Sciences), Tai’an 271016, China
关键词:
虚拟数字脑; 脑科学; 类脑人工智能; 因果连接网; 功能磁共振成像
Keywords:
Keywords: virtual digital brain;  brain science;  brain-inspired artificial intelligence;  causal connectivity network;  functional magnetic resonance imaging
分类号:
R312；TP391.4
DOI:
DOI:10.3969/j.issn.1005-202X.2019.12.013
文献标志码:
A
摘要:
目的：为脑科学和类脑人工智能提供一个软件研究平台。方法：首先，基于预处理后的静息态功能磁共振数据和因果连接法构建因果连接网，利用最小均方误差算法获得节点神经活动预测模型中的回归系数。然后，基于因果连接网和预测模型构建虚拟数字脑。最后，在VC++12.0开发环境下，利用C/C++编程语言开发出能实现虚拟数字脑各项功能的软件包。结果：同欧洲的虚拟大脑软件平台相比，该软件包操作简单，可用于脑科学和类脑人工智能的研究。结论：初步的实践结果证明了该软件在脑科学研究中的有效性和实际应用价值。
Abstract:
Abstract: Objective To provide a software research platform for brain science and brain-inspired artificial intelligence. Methods Firstly, a causal connection network was constructed on the basis of preprocessed resting-state functional magnetic resonance imaging data by a causal connectivity method. The regression coefficients of a nodal neural activity prediction model were obtained by the least-mean-square error algorithm. Then, the virtual digital brain was constructed based on the causal connection network and the prediction model. Finally, a software package which can implement all functions of virtual digital brain was developed by C/C++ programming language in the VC++12.0 development environment. Results Compared with the European virtual brain software platform, the proposed software package was easy to operate and could be applied to the researches on brain science and brain-inspired artificial intelligence. Conclusion The results of preliminary practices confirm the validity and application value of the software in the research on brain science.

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备注/Memo

备注/Memo:
【收稿日期】2019-08-17 【基金项目】山东省自然科学基金（ZR2018MH033, ZR2015HL095, ZR2014HM072）；山东省医药卫生科技发展计划项目（2016WS0608）；泰山医学院高层次课题培育计划项目（2018GCC13）；山东第一医科大学省级大学生创新创业训练计划项目（S201910439020） 【作者简介】徐龙春，副教授，主要从事脑功能成像和虚拟数字脑方面的研究，E-mail: xulongchun1971@163.com 【通信作者】张光玉，副教授，主要从事医学图像处理、脑功能成像和虚拟数字脑方面的研究，E-mail: gyuzhn@163.com
更新日期/Last Update: 2019-12-26