Parkinson's disease-related network topographies characterized with resting state functional MRI

Hum Brain Mapp. 2017 Feb;38(2):617-630. doi: 10.1002/hbm.23260. Epub 2016 May 21.


Spatial covariance mapping can be used to identify and measure the activity of disease-related functional brain networks. While this approach has been widely used in the analysis of cerebral blood flow and metabolic PET scans, it is not clear whether it can be reliably applied to resting state functional MRI (rs-fMRI) data. In this study, we present a novel method based on independent component analysis (ICA) to characterize specific network topographies associated with Parkinson's disease (PD). Using rs-fMRI data from PD and healthy subjects, we used ICA with bootstrap resampling to identify a PD-related pattern that reliably discriminated the two groups. This topography, termed rs-MRI PD-related pattern (fPDRP), was similar to previously characterized disease-related patterns identified using metabolic PET imaging. Following pattern identification, we validated the fPDRP by computing its expression in rs-fMRI testing data on a prospective case basis. Indeed, significant increases in fPDRP expression were found in separate sets of PD and control subjects. In addition to providing a similar degree of group separation as PET, fPDRP values correlated with motor disability and declined toward normal with levodopa administration. Finally, we used this approach in conjunction with neuropsychological performance measures to identify a separate PD cognition-related pattern in the patients. This pattern, termed rs-fMRI PD cognition-related pattern (fPDCP), was topographically similar to its PET-derived counterpart. Subject scores for the fPDCP correlated with executive function in both training and testing data. These findings suggest that ICA can be used in conjunction with bootstrap resampling to identify and validate stable disease-related network topographies in rs-fMRI. Hum Brain Mapp 38:617-630, 2017. © 2016 Wiley Periodicals, Inc.

Keywords: Parkinson's disease; biomarker; brain network; independent component analysis; resting state functional MRI; spatial covariance analysis.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Antiparkinson Agents / therapeutic use
  • Brain / diagnostic imaging*
  • Brain / drug effects
  • Brain Mapping
  • Cohort Studies
  • Female
  • Fluorodeoxyglucose F18
  • Humans
  • Image Processing, Computer-Assisted
  • Levodopa / therapeutic use
  • Logistic Models
  • Magnetic Resonance Imaging*
  • Male
  • Middle Aged
  • Neural Pathways / diagnostic imaging*
  • Oxygen / blood
  • Parkinson Disease / diagnostic imaging*
  • Parkinson Disease / drug therapy
  • Parkinson Disease / pathology*
  • Positron-Emission Tomography
  • Reproducibility of Results
  • Rest*


  • Antiparkinson Agents
  • Fluorodeoxyglucose F18
  • Levodopa
  • Oxygen