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Interindividual Differences in Functional Interactions among Prefrontal, Parietal and Parahippocampal Regions during Working Memory

To clarify the neural systems deployed by individual subjects during working memory (WM), we collected functional neuroimaging data from healthy subjects, and constructed a model of 2-back WM using structural equation modeling (SEM). A group model was constructed, and models for each subject were va...

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Bibliographic Details
Published in:Cerebral cortex (New York, N.Y. 1991) N.Y. 1991), 2003-12, Vol.13 (12), p.1352-1361
Main Authors: Glabus, Michael F., Horwitz, Barry, Holt, John L., Kohn, Philip D., Gerton, Brooke K., Callicott, Joseph H., Meyer-Lindenberg, Andreas, Berman, Karen Faith
Format: Article
Language:English
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Summary:To clarify the neural systems deployed by individual subjects during working memory (WM), we collected functional neuroimaging data from healthy subjects, and constructed a model of 2-back WM using structural equation modeling (SEM). A group model was constructed, and models for each subject were validated against it. The group model consisted principally of regions in the prefrontal and parietal cortex, with considerable interindividual variance in the single-subject models. To explore this variance, subjects were split into two groups based on performance. Performance level and self-reported strategy scores were used in a correlation analysis against path weights between nodes of individual models. High performers utilized a left hemisphere sub-network involving inferior parietal lobule and Broca’s area, whereas lower performers utilized a right hemisphere sub-network with interactions between inferior parietal lobule and dorsolateral prefrontal cortex. Further, we observed an interaction between the parahippocampal formation and the inferior parietal lobule that was related to the different strategies used by the individuals to perform the task. Strategy and performance level appear to be intricately related in this task, with neural systems supporting verbal processing producing better performance than those associated with spatial processing. These results demonstrate that individual behavioral characteristics are reflected in specific neurofunctional patterns at the system level and that these can be captured by analytical techniques such as SEM.
ISSN:1047-3211
1460-2199
1460-2199
DOI:10.1093/cercor/bhg082