Connectivity: Analysis
Mark Lowe1

1Cleveland Clinic Foundation, United States


An overview of current analysis methods for assessing functional connectivity using resting state fMRI data. A brief review of important preprocessing steps necessary for quality resting state data as well as various complex network analysis methods, including structural equation modeling, clustering methods and graph theoretic methods. Dynamic functional connectivity methods are briefly discussed.

Functional Connectivity with Resting State fMRI

  • Brief review(1,2)
  • Effect limited to (n < 0.1Hz) (4)
  • Brief review of suggested pre-processing pipeline Quality of results depends on high quality data preprocessing. Preprocessing steps can critically impact results(5) ·
  • Data: rapid (sms) or conventional Issues related to acquisition choice ·
  • Removing physiologic noise (6,7) RETROICOR, PESTICA RVT, CVT ·
  • Global signal ·
  • Vascular response ·
  • Example: HCP pipeline ·

Structural equation modeling(8) ·

Independent Components Analysis(9) ·

Clustering methods(10)

Methods based on spatiotemporal clustering

Graph Theoretic methods(11)

  • Parcellation methods(12) Graph theoretic methods require reduction of voxel level data into groups of nodes that must be homogeneous
  • Global network analysis(13) Functional integration of networks
  • Intermediate network analysis(14) Networks partitioned into modules and nodes (Rich club)
  • Local networks(15) Analyses of individual nodes

Dynamic Functional Connectivity(16)

Methods to examine nonstationary network behavior in resting state data


No acknowledgement found.


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Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)