Refined prefrontal working memory network as a neuromarker for Alzheimer’s disease
- 29 October 2021
- journal article
- research article
- Published by Optica Publishing Group in Biomedical Optics Express
- Vol. 12 (11), 7199-7222
- https://doi.org/10.1364/boe.438926
Abstract
Detecting Alzheimer's disease (AD) is an important step in preventing pathological brain damage. Working memory (WM)-related network modulation can be a pathological feature of AD, but is usually modulated by untargeted cognitive processes and individual variance, resulting in the concealment of this key information. Therefore, in this study, we comprehensively investigated a new neuromarker, named "refined network," in a prefrontal cortex (PFC) that revealed the pathological features of AD. A refined network was acquired by removing unnecessary variance from the WM-related network. By using a functional near-infrared spectroscopy (fNIRS) device, we evaluated the reliability of the refined network, which was identified from the three groups classified by AD progression: healthy people (N=31), mild cognitive impairment (N=11), and patients with AD (N=18). As a result, we identified edges with significant correlations between cognitive functions and groups in the dorsolateral PFC. Moreover, the refined network achieved a significantly correlating metric with neuropsychological test scores, and a remarkable three-class classification accuracy (95.0%). These results implicate the refined PFC WM-related network as a powerful neuromarker for AD screening. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing AgreementKeywords
Funding Information
- National Research Foundation of Korea (2017M3A9G8084463, 2017R1E1A1A01077393)
- Ministry of Science and ICT, South Korea (21-IJRP-01)
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