Using R to Estimate Dynamic Functional Connectivity for Brain Imaging Data
There are exciting applications of network science and graphical modeling in recent brain imaging studies. Watch as Ivor Cribben examines the challenges of estimating group-level dynamic connectivity structure across subjects and outlines novel data-driven statistical methods to estimate connectivity. Techniques discussed include:
- Working with fMRI and EEG data
- Graphical lasso, Stationary bootstrap, and Granger Causality
- R packages: glasso, gplot and JGL
This talk was given at the New York Open Statistical Programming Meetup at NYU Langone Medical Center.