A computational study of whole-brain connectivity in resting state and task fMRI

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A computational study of whole-brain connectivity in resting state and task fMRI

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Title: A computational study of whole-brain connectivity in resting state and task fMRI
Author: Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

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Citation: Goparaju, Balaji, Kunjan D. Rana, Finnegan J. Calabro, and Lucia Maria Vaina. 2014. “A computational study of whole-brain connectivity in resting state and task fMRI.” Medical Science Monitor : International Medical Journal of Experimental and Clinical Research 20 (1): 1024-1042. doi:10.12659/MSM.891142. http://dx.doi.org/10.12659/MSM.891142.
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Abstract: Background: We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results: In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions: In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition.
Published Version: doi:10.12659/MSM.891142
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4076230/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:12717603
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