阿尔兹海默症脑网络演化建模

倪冰洁; 李炜; 陈曦

doi:10.11959/j.issn.2096-6652.201941

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阿尔兹海默症脑网络演化建模

学术论文 | 更新时间：2024-06-05

- 阿尔兹海默症脑网络演化建模
- Brain network evolution modeling based on Alzheimer’s disease
- 智能科学与技术学报 2019年1卷第4期页码：369-378
- 作者机构：
  
  1. 华中科技大学人工智能与自动化学院，湖北武汉 430074
  2. 图像信息处理与智能控制教育部重点实验室，湖北武汉 430074
- 作者简介：
  
  [ "倪冰洁（1998- ），女，华中科技大学人工智能与自动化学院硕士生，主要研究方向为医学图像处理、模式识别" ]
  [ "李炜（1975- ），女，博士，华中科技大学人工智能与自动化学院教授，主要研究方向为神经影像分析、模式识别" ]
  [ "陈曦（1974- ），男，博士，华中科技大学人工智能与自动化学院教授，主要研究方向为复杂系统的建模与仿真" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61473131)
- DOI：10.11959/j.issn.2096-6652.201941
  中图分类号： TP29
- 网络出版日期：2019-12，
  
  纸质出版日期：2019-12-20
- 稿件说明：
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倪冰洁, 李炜, 陈曦. 阿尔兹海默症脑网络演化建模[J]. 智能科学与技术学报, 2019,1(4):369-378.

Bingjie NI, Wei LI, Xi CHEN. Brain network evolution modeling based on Alzheimer’s disease[J]. Chinese journal of intelligent science and technology, 2019, 1(4): 369-378.
倪冰洁, 李炜, 陈曦. 阿尔兹海默症脑网络演化建模[J]. 智能科学与技术学报, 2019,1(4):369-378. DOI： 10.11959/j.issn.2096-6652.201941.

Bingjie NI, Wei LI, Xi CHEN. Brain network evolution modeling based on Alzheimer’s disease[J]. Chinese journal of intelligent science and technology, 2019, 1(4): 369-378. DOI： 10.11959/j.issn.2096-6652.201941.

摘要

阿尔兹海默症作为一种常见且多发的疾病，严重影响着中老年群体的生活质量与水平，深入理解阿尔兹海默症的发病机制和发展进程对于研发相关预防措施及治疗手段非常重要。现有研究大多基于病变前后大脑静态特性的对照分析，忽略了其病变过程中的动态演化机制。基于功能磁共振成像数据构建大脑功能网络，对其病变过程纵向发展中神经系统动态演化过程进行深入研究，提出了一种基于脑网络水平的阿尔兹海默症病变过程的动态演化模型，以模拟大脑在神经系统病变过程中的动态演变及可塑过程，最后，从多个角度对演化结果进行评估，验证了模型的合理性，为阿尔兹海默症的早期诊断、功能评估及预测提供了新思路。

Abstract

As a common and frequently-occurring disease

Alzheimer’s disease seriously affects the quality and level of life of the middle-aged and elderly.An in-depth understanding of the pathogenesis and progression of Alzheimer’s disease is important for the development of prevention and treatment options.Most of the existing studies were based on the static property analysis of the brain network before and after the lesion

and dynamic evolutionary mechanism of the lesion process was usually neglected.A dynamic evolution model was proposed based on the level of brain networks of Alzheimer’s disease by analyzing the longitudinal development to simulate plastic changes of the process.Finally

the rationality of the model was verified by evaluating the evolutionary results from multiple perspectives.The study provides a new idea for early diagnosis

functional evaluation and prediction of Alzheimer’s disease.

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references

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