Uncovering Dynamic Functional Connectivity of Parkinson’s Disease Using Topological Features and Sparse Group Lasso

  • Kin Ming Puk
  • Wei Xiang
  • Shouyi WangEmail author
  • Cao (Danica) Xiao
  • W. A. Chaovalitwongse
  • Tara Madhyastha
  • Thomas Grabowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11309)


Neuro-degenerative diseases such as Parkinson’s Disease (PD) are clinically found to cause alternations and failures in brain connectivity. In this work, a new classification framework using dynamic functional connectivity and topological features is proposed, and it is shown that such framework can give better insights over discriminative difference of the disease itself. After utilizing sparse group lasso with anatomically labeled resting-state fMRI signal, both discriminating brain regions and voxels within can be identified easily. To give an overview of the effectiveness of such framework, the classification performance with the network features extracted on dynamic functional network is quantitatively evaluated. Experimental results show that either single feature of clustering coefficient or combined feature group of characteristic path length, diameter, eccentricity and radius perform well in classifying PD, and as a result the identified feature can lead to better interpretation for clinical purposes.


Parkinson’s disease Functional Magnetic Resonance Imaging (fMRI) Dynamic functional connectivity Sparse group lasso Classification 


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Kin Ming Puk
    • 1
  • Wei Xiang
    • 2
  • Shouyi Wang
    • 1
    Email author
  • Cao (Danica) Xiao
    • 3
  • W. A. Chaovalitwongse
    • 4
  • Tara Madhyastha
    • 5
  • Thomas Grabowski
    • 6
  1. 1.Department of Industrial, Manufacturing and Systems EngineeringUniversity of Texas at ArlingtonArlingtonUSA
  2. 2.Department of Computer Science and EngineeringUniversity of Texas at ArlingtonArlingtonUSA
  3. 3.AI for Healthcare, IBM ResearchYorktown HeightsUSA
  4. 4.Industrial EngineeringUniversity of Arkansas FayettevilleUSA
  5. 5.Integrated Brain Imaging CenterUniversity of WashingtonSeattleUSA
  6. 6.Departments of Radiology and NeurologyUniversity of WashingtonSeattleUSA

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