Extendable supervised dictionary learning for exploring diverse and concurrent brain activities in task-based fMRI.

Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional ma...

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Publicado en:Brain Imaging & Behavior Vol. 12; no. 3; pp. 743 - 758
Autores principales: Zhao, Shijie, Han, Junwei, Hu, Xintao, Jiang, Xi, Lv, Jinglei, Zhang, Tuo, Zhang, Shu, Guo, Lei, Liu, Tianming
Formato: Journal Article
Publicado: Springer Nature Jun2018
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Extendable supervised dictionary learning for exploring diverse and concurrent brain activities in task-based fMRI.
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          Zhao, Shijie
          Han, Junwei
          Hu, Xintao
          Jiang, Xi
          Lv, Jinglei
          Zhang, Tuo
          Zhang, Shu
          Guo, Lei
          Liu, Tianming
        affil: School of Automation, Northwestern Polytechnical University, Xi’an, China
      sug:
        subj:
          Mental Processes
          Brain Mapping Methods
          Brain
          Brain Physiology
          Magnetic Resonance Imaging Methods
          Hemodynamics
          Neural Pathways Physiology
          Neural Pathways
          Clinical Assessment Tools
          Questionnaires
      ab: Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional magnetic resonance imaging (tfMRI) analysis approach, i.e., the general linear model (GLM), might have difficulty in discovering those diverse and concurrent brain responses sufficiently. This subtraction-based model-driven approach focuses on the brain activities evoked directly from the task paradigm, thus likely overlooks other possible concurrent brain activities evoked during the information processing. To deal with this problem, in this paper, we propose a novel hybrid framework, called extendable supervised dictionary learning (E-SDL), to explore diverse and concurrent brain activities under task conditions. A critical difference between E-SDL framework and previous methods is that we systematically extend the basic task paradigm regressor into meaningful regressor groups to account for possible regressor variation during the information processing procedure in the brain. Applications of the proposed framework on five independent and publicly available tfMRI datasets from human connectome project (HCP) simultaneously revealed more meaningful group-wise consistent task-evoked networks and common intrinsic connectivity networks (ICNs). These results demonstrate the advantage of the proposed framework in identifying the diversity of concurrent brain activities in tfMRI datasets.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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