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dc.contributor.authorLebedev, Alexanderen_US
dc.contributor.authorWestman, Ericen_US
dc.contributor.authorSimmons, Andrewen_US
dc.contributor.authorLebedeva, Aleksandraen_US
dc.contributor.authorSiepel, Françoise J.en_US
dc.contributor.authorPereira, Joana B.en_US
dc.contributor.authorAarsland, Dagen_US
dc.date.accessioned2014-09-15T12:10:19Z
dc.date.available2014-09-15T12:10:19Z
dc.date.issued2014-04-03eng
dc.identifier.issn1662-5137
dc.identifier.urihttps://hdl.handle.net/1956/8472
dc.description.abstractCognitive impairment is a common non-motor feature of Parkinson’s disease (PD). Understanding the neural mechanisms of this deficit is crucial for the development of efficient methods for treatment monitoring and augmentation of cognitive functions in PD patients. The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson’s Progression Marker Initiative (PPMI) database. Eighteen patients from this sample were also scanned with ¹²³I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs) defined from the AAL brain atlas. The Brain Connectivity Toolbox (BCT) was used to extract nodal strength from all ROIs, and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable (LV) scores were matched with the performances in the three cognitive domains (memory, visuospatial, and executive) and striatal dopamine transporter binding ratios (SBR) using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on the modularity of the “cognitive network” was analyzed. For the range of deficits studied, better executive performance was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This profile was also characterized by a relative preservation of nigrostriatal dopaminergic function. The profile associated with better memory performance correlated with increased prefronto-limbic processing, and was not associated with presynaptic striatal dopamine uptake. SBR ratios were negatively correlated with modularity of the “cognitive network,” suggesting integrative effects of the preserved nigrostriatal dopamine system on this circuitry.en_US
dc.language.isoengeng
dc.publisherFrontierseng
dc.relation.ispartof<a href="http://hdl.handle.net/1956/8473" target="blank">Cognitive impairment in neurodegenerative diseases: insights from computational neuroimaging</a>eng
dc.rightsAttribution CC BYeng
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/eng
dc.subjectParkinson’s diseaseeng
dc.subjectCognitioneng
dc.subjectDopamineeng
dc.subjectResting state fMRIeng
dc.subjectSPECTeng
dc.subjectGraph theoryeng
dc.subjectNodal strengtheng
dc.subjectModularityeng
dc.titleLarge-scale resting state network correlates of cognitive impairment in Parkinson’s disease and related dopaminergic deficitsen_US
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2014 Lebedev, Westman, Simmons, Lebedeva, Siepel, Pereira and Aarsland.
dc.source.articlenumber45
dc.identifier.doihttps://doi.org/10.3389/fnsys.2014.00045
dc.source.journalFrontiers in Systems Neuroscience
dc.source.408


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