Fusing Functional MRI and Diffusion Tensor Imaging Measures of Brain Function and Structure to Predict Working Memory and Processing Speed Performance among Inter-episode Bipolar XXXX .

@entity1 @entity162 @entity75 @entity73 @entity3057
UNASSIGNED: Evidence for abnormal brain function as measured with diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) and @entity73 have been observed in inter-episode @entity162 ( @entity162 ) @entity1 . We aimed to create a joint statistical model of white matter integrity and functional response measures in explaining differences in working memory and processing speed among @entity162 @entity1 . Medicated inter-episode @entity162 (n=26; age=45.2  10.1 years) and healthy comparison (HC; n=36; age=46.3  11.5 years) @entity1 completed 51-direction DTI and fMRI while performing a working memory task. @entity1 also completed a processing speed test. Tract-based spatial statistics identified common white matter tracts where fractional anisotropy was calculated from atlas-defined regions of interest. Brain responses within regions of interest activation clusters were also calculated. Least angle regression was used to fuse fMRI and DTI data to select the best joint neuroimaging predictors of cognitive performance for each group. While there was overlap between groups in which regions were most related to cognitive performance, some relationships differed between groups. For working memory accuracy, @entity162 -specific predictors included bilateral dorsolateral prefrontal cortex from fMRI, splenium of the corpus callosum, left uncinate fasciculus, and bilateral superior longitudinal fasciculi from DTI. For processing speed, the genu and splenium of the corpus callosum and right superior @entity3057 from DTI were significant predictors of cognitive performance selectively for @entity162 @entity1 . @entity162 @entity1 demonstrated unique brain-cognition relationships compared to HC. These findings are a first step in discovering how interactions of structural and functional @entity75 contribute to @entity73 in @entity162 . (JINS, 2015, 21, 330-341).
