A semi-blind online dictionary learning approach for fMRI data.

Journal: Journal of neuroscience methods
Published Date: May 11, 2019

Abstract

BACKGROUND: Online dictionary learning (ODL) has been applied to extract brain networks from functional magnetic resonance imaging (fMRI) data in recent year. Moreover, the supervised dictionary learning (SDL) that fixed the task stimulus curves as predefined atoms was proposed to improve ODL for functional networks separation. However, SDL cannot estimate the real time courses underlying the brain networks and cannot be applied to the inter-network connectivity analysis. This study aimed at investigating how to add the temporal prior information to ODL to extract the accurate task-related brain networks and the corresponding time courses.

Authors

  • Zhiying Long
    State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
  • Lu Liu
    College of Pharmacy, Harbin Medical University, Harbin, China.
  • Zhe Gao
    State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
  • Maoming Chen
    State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
  • Li Yao
    College of Information Science and Technology, Beijing Normal University, Beijing, China.

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