Skip to content

MATLAB scripts for the arousal-level-dependent hub analysis of fMRI data using pupillometry

License

Notifications You must be signed in to change notification settings

Kangjoo/arousal-rsfMRIpupil-hub

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

27 Commits
 
 
 
 
 
 
 
 

Repository files navigation

arousal-rsfMRIpupil-hub

  • SPARK_fMRI_pupillometry.m performs a four-step analysis:

       STEP 1. Pupillometry processing
       STEP 2. State stratification of fMRI data using pupillometry
       STEP 3. Bootstrap resampling of state-stratified fMRI data
       STEP 4. Sparse dictionary learning of resampled data
    
  • Other scripts to implement the remainings of the SPARK analysis, such as the parallel implementation of the sparse dictionary learning, spatial K-means clustering, background noise removal, and k-hubness estimation, can be found and adapted from SPARK.

  • SPARK_HDI.m computes the hub disruption index (HDI) to compare k-hubness estimated from fMRI data in two arousal states, e.g., high and low arousal.

For further questions please raise an issue here


Requirements

  • SParsity-based Analysis of Reliable K-hubness (SPARK)

  • SPM8 or SPM12 is required to process pupillometry data.


Citation

If you use this library for your publications, please cite it as:

Kangjoo Lee, Corey Horien, David O’Connor, Bronwen Garand-Sheridan, Fuyuze Tokoglu, Dustin Scheinost, Evelyn M.R. Lake, R. Todd Constable, “Arousal impacts distributed hubs modulating the integration of brain functional connectivity”, Neuroimage (2022), Link.

About

MATLAB scripts for the arousal-level-dependent hub analysis of fMRI data using pupillometry

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages