Meta-Analysis of Functional Roles of DICCCOLs
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  • 作者:Yixuan Yuan (1)
    Xi Jiang (2)
    Dajiang Zhu (2)
    Hanbo Chen (2)
    Kaiming Li (1) (2)
    Peili Lv (1)
    Xiang Yu (1)
    Xiaojin Li (1)
    Shu Zhang (1)
    Tuo Zhang (1) (2)
    Xintao Hu (1)
    Junwei Han (1)
    Lei Guo (1)
    Tianming Liu (2)
  • 关键词:Structural connectivity ; Functional connectivity ; Brain networks
  • 刊名:Neuroinformatics
  • 出版年:2013
  • 出版时间:January 2013
  • 年:2013
  • 卷:11
  • 期:1
  • 页码:47-63
  • 全文大小:1614KB
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  • 作者单位:Yixuan Yuan (1)
    Xi Jiang (2)
    Dajiang Zhu (2)
    Hanbo Chen (2)
    Kaiming Li (1) (2)
    Peili Lv (1)
    Xiang Yu (1)
    Xiaojin Li (1)
    Shu Zhang (1)
    Tuo Zhang (1) (2)
    Xintao Hu (1)
    Junwei Han (1)
    Lei Guo (1)
    Tianming Liu (2)

    1. School of Automation, Northwestern Polytechnical University, Xi’an, China
    2. Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
  • ISSN:1559-0089
文摘
DICCCOL (Dense Individualized and Common Connectivity-based Cortical Landmarks) is a recently published system composed of 358 cortical landmarks that possess consistent correspondences across individuals and populations. Meanwhile, each DICCCOL landmark is localized in an individual brain’s unique morphological profile, and therefore the DICCCOL system offers a universal and individualized brain reference and localization framework. However, in current 358 diffusion tensor imaging (DTI)-derived DICCCOLs, only 95 of them have been functionally annotated via task-based or resting-state fMRI datasets and the functional roles of other DICCCOLs are unknown yet. This work aims to take the advantage of existing literature fMRI studies (1110 publications) reported and aggregated in the BrainMap database to examine the possible functional roles of 358 DICCCOLs via meta-analysis. Our experimental results demonstrate that a majority of 358 DICCCOLs can be functionally annotated by the BrainMap database, and many DICCCOLs have rich and diverse functional roles in multiple behavior domains. This study provides novel insights into the functional regularity and diversity of 358 DICCCOLs, and offers a starting point for future elucidation of fine-grained functional roles of cortical landmarks.

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