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https://hdl.handle.net/10356/141600
Title: | Altered intra- and inter-hemispheric functional dysconnectivity in schizophrenia | Authors: | Zhang, Yuan Dai, Zhongxiang Chen, Yu Sim, Kang Sun, Yu Yu, Rongjun |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2018 | Source: | Zhang, Y., Dai, Z., Chen, Y., Sim, K., Sun, Y., & Yu, R. (2019). Altered intra- and inter-hemispheric functional dysconnectivity in schizophrenia. Brain Imaging and Behavior, 13(5), 1220-1235. doi:10.1007/s11682-018-9935-8 | Journal: | Brain Imaging and Behavior | Abstract: | Despite convergent evidence suggesting that schizophrenia is a disorder of brain dysconnectivity, it remains unclear whether intra- or inter-hemispheric deficits or their combination underlie the dysconnection. This study examined the source of the functional dysconnection in schizophrenia. Resting-state fMRI was performed in 66 patients with schizophrenia and 73 matched healthy controls. Functional brain networks were constructed for each participant and further partitioned into intra- and inter-hemispheric connections. We examined how schizophrenia altered the intra-hemispheric topological properties and the inter-hemispheric nodal strength. Although several subcortical and cingulate regions exhibited hemispheric-independent aberrations of regional efficiency, the optimal small-world properties in the hemispheric networks and their lateralization were preserved in patients. A significant deficit in the inter-hemispheric connectivity was revealed in most of the hub regions, leading to an inter-hemispheric hypo-connectivity pattern in patients. These abnormal intra- and inter-hemispheric network organizations were associated with the clinical features of schizophrenia. The patients in the present study received different medications. These findings provide new insights into the nature of dysconnectivity in schizophrenia, highlighting the dissociable processes between the preserved intra-hemispheric network topology and altered inter-hemispheric functional connectivity. | URI: | https://hdl.handle.net/10356/141600 | ISSN: | 1931-7557 | DOI: | 10.1007/s11682-018-9935-8 | Schools: | School of Computer Science and Engineering | Rights: | © 2018 Springer Science+Business Media, LLC, part of Springer Nature. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
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