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dc.contributor.authorDauvermann, Maria R.
dc.contributor.authorMoorhead, Thomas WJ
dc.contributor.authorWatson, Andrew R.
dc.contributor.authorDuff, Barbara
dc.contributor.authorRomaniuk, Liana
dc.contributor.authorHall, Jeremy
dc.contributor.authorRoberts, Neil
dc.contributor.authorLee, Graham L.
dc.contributor.authorHughes, Zoë A.
dc.contributor.authorBrandon, Nicholas J.
dc.contributor.authorWhitcher, Brandon
dc.contributor.authorBlackwood, Douglas HR
dc.contributor.authorMcIntosh, Andrew M.
dc.contributor.authorLawrie, Stephen M.
dc.date.accessioned2018-09-20T16:05:12Z
dc.date.available2018-09-20T16:05:12Z
dc.date.issued2017-12-01
dc.identifier.citationDauvermann, Maria R. Moorhead, Thomas WJ; Watson, Andrew R.; Duff, Barbara; Romaniuk, Liana; Hall, Jeremy; Roberts, Neil; Lee, Graham L.; Hughes, Zoë A.; Brandon, Nicholas J.; Whitcher, Brandon; Blackwood, Douglas HR; McIntosh, Andrew M.; Lawrie, Stephen M. (2017). Verbal working memory and functional large-scale networks in schizophrenia. Psychiatry Research: Neuroimaging 270 , 86-96
dc.identifier.issn0925-4927
dc.identifier.urihttp://hdl.handle.net/10379/11070
dc.description.abstractThe aim of this study was to test whether bilinear and nonlinear effective connectivity (EC) measures of working memory fMRI data can differentiate between patients with schizophrenia (SZ) and healthy controls (HC). We applied bilinear and nonlinear Dynamic Causal Modeling (DCM) for the analysis of verbal working memory in 16 SZ and 21 HC. The connection strengths with nonlinear modulation between the dorsolateral prefrontal cortex (DLPFC) and the ventral tegmental area/substantia nigra (VTA/SN) were evaluated. We used Bayesian Model Selection at the group and family levels to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging was used to assess the connection strengths with nonlinear modulation. The DCM analyses revealed that SZ and HC used different bilinear networks despite comparable behavioral performance. In addition, the connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area showed differences between SZ and HC. The adoption of different functional networks in SZ and HC indicated neurobiological alterations underlying working memory performance, including different connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area. These novel findings may increase our understanding of connectivity in working memory in schizophrenia.
dc.publisherElsevier BV
dc.relation.ispartofPsychiatry Research: Neuroimaging
dc.subjectworking memory
dc.subjectschizophrenia
dc.subjectfunctional magnetic resonance imaging
dc.subjectfunctional large-scale networks
dc.subjectnonlinear dynamic causal modeling
dc.subjectmagnetic-resonance spectroscopy
dc.subjectventral tegmental area
dc.subjectdynamic causal-models
dc.subjectdopamine-glutamate interactions
dc.subjectaltered effective connectivity
dc.subjectprefrontal cortex neurons
dc.subjectsynaptic plasticity
dc.subjectcognitive impairment
dc.subjectmidbrain dopamine
dc.subjectgain modulation
dc.titleVerbal working memory and functional large-scale networks in schizophrenia
dc.typeArticle
dc.identifier.doi10.1016/j.pscychresns.2017.10.004
dc.local.publishedsourcehttps://doi.org/10.1016/j.pscychresns.2017.10.004
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