Abstract
In this manuscript we consider the problem of relating functional connectivity measurements viewed as statistical distributions to outcomes. We demonstrate the utility of using the distribution of connectivity on a study of resting state functional magnetic resonance imaging association with an intervention. Specifically, we consider 47 primary progressive aphasia (PPA) patients with various levels of language abilities. These patients were randomly assigned to two treatment arms, tDCS (transcranial direct-current stimulation and language therapy) vs sham (language therapy only), in a clinical trial. We propose a novel approach to analyze the effect of direct stimulation on functional connectivity. We estimate the density of correlations among the regions of interest (ROIs) and study the difference in the density post-intervention between treatment arms. We discover that it is the tail of the density, rather than the mean or lower order moments of the distribution, that demonstrates a significant impact in the classification. This approach has several benefits. Among them, it drastically reduces the number of multiple comparisons compared to edge-wise analysis. In addition, it allows for the investigation of the impact of functional connectivity on the outcomes where the connectivity is not geometrically localized.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Email address: bhtang{at}jhu.edu (Bohao Tang)
