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Refined prefrontal working memory network as a neuromarker for Alzheimer's disease
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Eunho | - |
dc.contributor.author | Yu, Jin-Woo | - |
dc.contributor.author | Kim, Bomin | - |
dc.contributor.author | Lim, Sung-Ho | - |
dc.contributor.author | Lee, Sang-Ho | - |
dc.contributor.author | Kim, Kwangsu | - |
dc.contributor.author | Son, Gowoon | - |
dc.contributor.author | Jeon, Hyeon-Ae | - |
dc.contributor.author | Moon, Cheil | - |
dc.contributor.author | Sakong, Joon | - |
dc.contributor.author | Choi, Ji-Woong | - |
dc.date.accessioned | 2024-04-30T01:20:31Z | - |
dc.date.available | 2024-04-30T01:20:31Z | - |
dc.date.created | 2024-04-30 | - |
dc.date.issued | 2021-11 | - |
dc.identifier.citation | BIOMEDICAL OPTICS EXPRESS, Vol.12 No.11, pp.7199-7222 | - |
dc.identifier.issn | 2156-7085 | - |
dc.identifier.uri | https://hdl.handle.net/10371/199951 | - |
dc.description.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 Agreement | - |
dc.language | 영어 | - |
dc.publisher | Optica Publishing Group | - |
dc.title | Refined prefrontal working memory network as a neuromarker for Alzheimer's disease | - |
dc.type | Article | - |
dc.identifier.doi | 10.1364/BOE.438926 | - |
dc.citation.journaltitle | BIOMEDICAL OPTICS EXPRESS | - |
dc.identifier.wosid | 000717641100004 | - |
dc.identifier.scopusid | 2-s2.0-85118407157 | - |
dc.citation.endpage | 7222 | - |
dc.citation.number | 11 | - |
dc.citation.startpage | 7199 | - |
dc.citation.volume | 12 | - |
dc.description.isOpenAccess | Y | - |
dc.contributor.affiliatedAuthor | Jeon, Hyeon-Ae | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordPlus | MILD COGNITIVE IMPAIRMENT | - |
dc.subject.keywordPlus | NEAR-INFRARED SPECTROSCOPY | - |
dc.subject.keywordPlus | FUNCTIONAL CONNECTIVITY | - |
dc.subject.keywordPlus | EARLY-DIAGNOSIS | - |
dc.subject.keywordPlus | BRAIN ACTIVITY | - |
dc.subject.keywordPlus | DEFAULT MODE | - |
dc.subject.keywordPlus | FNIRS | - |
dc.subject.keywordPlus | DECLINE | - |
dc.subject.keywordPlus | STATE | - |
dc.subject.keywordPlus | FMRI | - |
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