• Title/Summary/Keyword: Independet Component Analysis

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Combined Analysis Using Functional Connectivity of Default Mode Network Based on Independent Component Analysis of Resting State fMRI and Structural Connectivity Using Diffusion Tensor Imaging Tractography (휴지기 기능적 자기공명영상의 독립성분분석기법 기반 내정상태 네트워크 기능 연결성과 확산텐서영상의 트랙토그래피 기법을 이용한 구조 연결성의 통합적 분석)

  • Choi, Hyejeong;Chang, Yongmin
    • Journal of Korea Multimedia Society
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    • v.24 no.5
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    • pp.684-694
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    • 2021
  • Resting-state Functional Magnetic Resonance Imaging(fMRI) data detects the temporal correlations in Blood Oxygen Level Dependent(BOLD) signal and these temporal correlations are regarded to reflect intrinsic cortical connectivity, which is deactivated during attention demanding, non-self referential tasks, called Default Mode Network(DMN). The relationship between fMRI and anatomical connectivity has not been studied in detail, however, the preceded studies have tried to clarify this relationship using Diffusion Tensor Imaging(DTI) and fMRI. These studies use method that fMRI data assists DTI data or vice versa and it is used as guider to perform DTI tractography on the brain image. In this study, we hypothesized that functional connectivity in resting state would reflect anatomical connectivity of DMN and the combined images include information of fMRI and DTI showed visible connection between brain regions related in DMN. In the previous study, functional connectivity was determined by subjective region of interest method. However, in this study, functional connectivity was determined by objective and advanced method through Independent Component Analysis. There was a stronger connection between Posterior Congulate Cortex(PCC) and PHG(Parahippocampa Gyrus) than Anterior Cingulate Cortex(ACC) and PCC. This technique might be used in several clinical field and will be the basis for future studies related to aging and the brain diseases, which are needed to be translated not only functional connectivity, but structural connectivity.