Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm.

ABSTRACT: Resting state functional connectivity MRI (rs-fcMRI) is a popular technique used to gauge the functional relatedness between regions in the brain for typical and special populations. Most of the work to date determines this relationship by using Pearson's correlation on BOLD fMRI timeseries. However, it has been recognized that there are at least two key limitations to this method. First, it is not possible to resolve the direct and indirect connections/influences. Second, the direction of information flow between the regions cannot be differentiated. In the current paper, we follow-up on recent work by Smith et al. (2011), and apply PC algorithm to both simulated data and empirical data to determine whether these two factors can be discerned with group average, as opposed to single subjec

SUBMITTER: Iyer SP 

PROVIDER: S-EPMC3683082 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature