Olusola Ajilore1, Nathalie Vizueta2, Patricia Walshaw2, Liang Zhan3, Alex Leow4, Lori L Altshuler2. 1. Department of Psychiatry, University of Illinois, College of Medicine, United States. 2. Department of Psychiatry and Biobehavioral Sciences, UCLA Semel Institute for Neuroscience & Human Behavior, United States. 3. Department of Neurology, University of California, Los Angeles, United States. 4. Department of Psychiatry, University of Illinois, College of Medicine, United States; Department of Bioengineering, University of Illinois, College of Medicine, United States. Electronic address: alexfeuillet@gmail.com.
Abstract
OBJECTIVES: Connectomics have allowed researchers to study integrative patterns of neural connectivity in humans. Yet, it is unclear how connectomics may elucidate structure-function relationships in bipolar I disorder (BPI). Expanding on our previous structural connectome study, here we used an overlapping sample with additional psychometric and fMRI data to relate structural connectome properties to both fMRI signals and cognitive performance. METHODS: 42 subjects completed a neuropsychological (NP) battery covering domains of processing speed, verbal memory, working memory, and cognitive flexibility. 32 subjects also had fMRI data performing a Go/NoGo task. RESULTS: Bipolar participants had lower NP performance across all domains, but only working memory reached statistical significance. In BPI participants, processing speed was significantly associated with both white matter integrity (WMI) in the corpus callosum and interhemispheric network integration. Mediation models further revealed that the relationship between interhemispheric integration and processing speed was mediated by WMI, and processing speed mediated the relationship between WMI and working memory. Bipolar subjects had significantly decreased BA47 activation during NoGo vs. Go. Significant predictors of BA47 fMRI activations during the Go/NoGo task were its nodal path length (left hemisphere) and its nodal clustering coefficient (right hemisphere). CONCLUSIONS: This study suggests that structural connectome changes underlie abnormalities in fMRI activation and cognitive performance in euthymic BPI subjects. Results support that BA47 structural connectome changes may be a trait marker for BPI. Future studies are needed to determine if these "connectome signatures" may also confer a biological risk and/or serve as predictors of relapse.
OBJECTIVES: Connectomics have allowed researchers to study integrative patterns of neural connectivity in humans. Yet, it is unclear how connectomics may elucidate structure-function relationships in bipolar I disorder (BPI). Expanding on our previous structural connectome study, here we used an overlapping sample with additional psychometric and fMRI data to relate structural connectome properties to both fMRI signals and cognitive performance. METHODS: 42 subjects completed a neuropsychological (NP) battery covering domains of processing speed, verbal memory, working memory, and cognitive flexibility. 32 subjects also had fMRI data performing a Go/NoGo task. RESULTS: Bipolar participants had lower NP performance across all domains, but only working memory reached statistical significance. In BPI participants, processing speed was significantly associated with both white matter integrity (WMI) in the corpus callosum and interhemispheric network integration. Mediation models further revealed that the relationship between interhemispheric integration and processing speed was mediated by WMI, and processing speed mediated the relationship between WMI and working memory. Bipolar subjects had significantly decreased BA47 activation during NoGo vs. Go. Significant predictors of BA47 fMRI activations during the Go/NoGo task were its nodal path length (left hemisphere) and its nodal clustering coefficient (right hemisphere). CONCLUSIONS: This study suggests that structural connectome changes underlie abnormalities in fMRI activation and cognitive performance in euthymic BPI subjects. Results support that BA47 structural connectome changes may be a trait marker for BPI. Future studies are needed to determine if these "connectome signatures" may also confer a biological risk and/or serve as predictors of relapse.
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