Exploring Brain Regions Related to Azheimer's Disease Using Functional Data Analysis Approach on Resting-State fMRI Data

• 영문명: Exploring Brain Regions Related to Azheimer's Disease Using Functional Data Analysis Approach on Resting-State fMRI Data
• 발행기관: 한국자료분석학회
• 저자명: Ido Ji Eunjee Lee
• 간행물 정보: 『한국자료분석학회 학술대회자료집』2023년 동계학술대회 발표집, 33~36쪽, 전체 4쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2023.12.31

국문 초록

Alzheimer's Disease (AD) is a burdensome and incurable neurodegenerative disease, so brain study is needed to understand its pathogenesis. Since functional connectivity (FC) alteration has been shown in among AD patients groups, Resting-State fMRI (RS-fMRI) was used to explore brain regions. However, the previous study overlooked continuity on brain regions in FC analysis. From a study who introduced euclidean distance in FC analysis, we also employed a similar method and obtained FC curves. Since these curves can be considered to be functions, functional data analysis (FDA) was employed to treat this type of data. Especially, functional principal component analysis (FPCA) was used to extract function PC (fPC) scores from each brain region. These scores were used as covariates in logistic regression models with group penalties. Compared to the former approaches, our method showed higher classification rate in normal controls and AD patients (AUC = 0.9). Also, brain regions related to neurodegenerative studies were chosen in our best model. However, there were cases where only one side of the region was chosen. Hence further study is needed on these regions in our future work.

키워드

Alzheimer’s Disease Resting-State fMRI Functional Connectivity Euclidean Distance Functional Data Analysis