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 subject, functional connectivity data. When applied on simulated individual subjects, the algorithm performs well determining indirect and direct connection but fails in determining directionality. However, when applied at group level, PC algorithm gives strong results for both indirect and direct connections and the direction of information flow. Applying the algorithm on empirical data, using a diffusion-weighted imaging (DWI) structural connectivity matrix as the baseline, the PC algorithm outperformed the direct correlations. We conclude that, under certain conditions, the PC algorithm leads to an improved estimate of brain network structure compared to the traditional connectivity analysis based on correlations.
Original language | English (US) |
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Pages (from-to) | 165-175 |
Number of pages | 11 |
Journal | NeuroImage |
Volume | 75 |
DOIs | |
State | Published - Jul 15 2013 |
Externally published | Yes |
Bibliographical note
Funding Information:This research was supported by R00 MH091238 (Fair), R01 MH096773 (Fair), R01 MH086654 (Nigg), Oregon Clinical and Translational Institute (Fair), K25 AG033723 (Shafran) and McDonnell Foundation (Petersen/Sporns/Fair). We thank Corinne Stevens, Sam Carpenter and Taciana Costa Dias for their important discussions and help with data collection.
Keywords
- Bayesian network
- Directed functional connectivity
- Effective connectivity
- FMRI
- PC algorithm