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ORIGINAL RESEARCH article

Front. Aging Neurosci.
Sec. Alzheimer's Disease and Related Dementias
Volume 16 - 2024 | doi: 10.3389/fnagi.2024.1469620
This article is part of the Research Topic Advancing Early Alzheimer's Detection Through Multimodal Neuroimaging Techniques View all articles

Research on the Application of Functional Near-Infrared Spectroscopy in Differentiating Subjective Cognitive Decline and Mild Cognitive Impairment

Provisionally accepted
Zheng Wang Zheng Wang 1Chaojie Niu Chaojie Niu 2Yong Duan Yong Duan 2Hao Yang Hao Yang 3*Jinpeng Mi Jinpeng Mi 4*Chao Liu Chao Liu 2*Guodong Chen Guodong Chen 2*Qihao Guo Qihao Guo 1*
  • 1 Department of Gerontology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
  • 2 School of Mechanical and Electrical Engineering, Jiangsu Provincial Key Labratory of Advanced Robotics, & Robotics and Microsystems Center, Soochow University, Suzhou 215123, China
  • 3 School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
  • 4 Institute of Machine Intelligence (IMI), University of Shanghai for Science and Technology, Shanghai, China

The final, formatted version of the article will be published soon.

    Alzheimer's disease (AD) is a common neurological disorder. Based on clinical characteristics, it can be categorized into normal cognition (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia (AD). Once the condition begins to progress, the process is usually irreversible. Therefore, early identification and intervention are crucial for patients. This study aims to explore the sensitivity of fNIRS in distinguishing between SCD and MCI. An in-depth analysis of the Functional Connectivity(FC) and oxygenated hemoglobin (HbO) characteristics during resting state and different memory cognitive tasks is conducted on two patient groups to search for potential biomarkers. The 33 participants were divided into two groups: SCD and MCI. Functional connectivity strength during the resting state and hemodynamic changes during the execution of Verbal Fluency Tasks (VFT) and MemTrax tasks were measured using fNIRS. The results showed that compared to individuals with MCI, patients with SCD exhibited higher average FC levels between different channels in the frontal lobe during resting state, with two channels' FC demonstrating significant ability to distinguish between SCD and MCI. During the VFT task, the overall average HbO concentration in the frontal lobe of SCD patients was higher than that of MCI patients from 5Experimental ParadigmReceiver operating characteristic analysis indicated that the accuracy of the above features in distinguishing SCD from MCI was 78.8%, 72.7%, 75.8%, and 66.7%, respectively. fNIRS could potentially serve as a non-invasive biomarker for the early detection of dementia.

    Keywords: functional near-infrared spectroscopy, MCI, SCD, Alzheimer's disease, early diagnosis

    Received: 24 Jul 2024; Accepted: 11 Dec 2024.

    Copyright: © 2024 Wang, Niu, Duan, Yang, Mi, Liu, Chen and Guo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Hao Yang, School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
    Jinpeng Mi, Institute of Machine Intelligence (IMI), University of Shanghai for Science and Technology, Shanghai, China
    Chao Liu, School of Mechanical and Electrical Engineering, Jiangsu Provincial Key Labratory of Advanced Robotics, & Robotics and Microsystems Center, Soochow University, Suzhou 215123, China
    Guodong Chen, School of Mechanical and Electrical Engineering, Jiangsu Provincial Key Labratory of Advanced Robotics, & Robotics and Microsystems Center, Soochow University, Suzhou 215123, China
    Qihao Guo, Department of Gerontology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China

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