Target localization intervention and prognosis evaluation for an individual with mild cognitive impairment

Author:

Wang Weiping123ORCID,Zhao Haiyan4,He Chang123ORCID,Cui Yuanbo5,Wang Zhen6,Hramov Alexander78,Luan Ping9,Luo Xiong123,Ouyang Jipeng10,Jürgen Kurths1112

Affiliation:

1. School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

2. Shunde Graduate School University of Science and Technology Beijing Foshan Guangdong China

3. Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China

4. Department of Neurology Peking University Third Hospital Beijing China

5. The 6th Research Institute of China Electronics Corporation Beijing China

6. The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi China

7. Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

8. Saratov State Medical University Saratov Russia

9. Guangdong Second Provincial General Hospital & Health Science Center Shenzhen Guangdong China

10. Department of Neurology Shunde Hospital Southern Medical University Foshan Guangdong China

11. Institute of Physics Humboldt‐University Berlin Germany

12. Potsdam Institute for Climate Impact Research Potsdam Germany

Abstract

AbstractCurrently, no specific treatments are available for Alzheimer's disease (AD). Mild cognitive impairment (MCI), the preclinical stage of AD, has a high possibility of reversing symptoms through neural regulation. A state dynamics model for single brain regions was developed to simulate blood oxygen level‐dependent signals in a patient with early mild cognitive impairment. Subsequently, the analysis of functional connections was used to comprehensively consider multiple complex network centralities to locate the intervention targets, and a multiple brain region collaborative control scheme was designed. Finally, the reliability and effectiveness of the intervention were verified at the brain region and subnetwork levels. This technique provides a basis for future clinical diagnosis and treatment of AD and MCI.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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