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dc.contributor.authorHajebrahimi, Farzin
dc.contributor.authorBudak, Miray
dc.contributor.authorSaricaoglu, Mevhibe
dc.contributor.authorTemel, Zeynep
dc.contributor.authorDemir, Tugce Kahraman
dc.contributor.authorHanoglu, Lutfu
dc.contributor.authorYildirim, Suleyman
dc.contributor.authorBayraktaroglu, Zubeyir
dc.date.accessioned2024-02-02T11:03:35Z
dc.date.available2024-02-02T11:03:35Z
dc.date.issued2024en_US
dc.identifier.citationHAJEBRAHIMI, Farzin, Miray BUDAK, Mevhibe SARICAOĞLU, Zeynep TEMEL, Tuğce Kahraman DEMİR, Lütfü HANOĞLU, Suleyman YILDIRIM & Zübeyir BAYRAKTAROĞLU. "Functional Neural Networks Stratify Parkinson’s Disease Patients Across the Spectrum of Cognitive Impairment". Brain and Behavior, 14.1 (2023): 1-19.en_US
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/10.1002/brb3.3384
dc.identifier.urihttps://hdl.handle.net/11352/4717
dc.description.abstractIntroduction: Cognitive impairment (CI) is a significant non-motor symptoms inParkinson’s disease (PD) that often precedes the emergence of motor symptoms by several years. Patients with PD hypothetically progress from stages without CI (PD-normal cognition [NC]) to stageswithMild CI (PD-MCI) and PDdementia (PDD). CI symptoms in PD are linked to different brain regions and neural pathways, in addition to being the result of dysfunctional subcortical regions. However, it is still unknown how functional dysregulation correlates to progression during the CI. Neuroimaging techniques hold promise in discriminating CI stages of PD and further contribute to the biomarker formation of CI in PD. In this study, we explore disparities in the clinical assessments and resting-state functional connectivity (FC) among three CI stages of PD. Methods: We enrolled 88 patients with PD and 26 healthy controls (HC) for a cross sectional clinical study and performed intra- and inter-network FC analysis in conjunction with comprehensive clinical cognitive assessment. Results: Our findings underscore the significance of several neural networks, namely, the default mode network (DMN), frontoparietal network (FPN), dorsal attention network, and visual network (VN) and their inter–intra-network FC in differentiating between PD-MCI and PDD. Additionally, our results showed the importance of sensory motor network, VN,DMN, and salience network (SN) in the discriminating PD-NC from PDD. Finally, in comparison to HC, we found DMN, FPN, VN, and SN as pivotal networks for further differential diagnosis of CI stages of PD. Conclusion:We propose that resting-state networks (RSN) can be a discriminating factor in distinguishing the CI stages of PD and progressing from PD-NC toMCI or PDD. The integration of clinical and neuroimaging data may enhance the early detection of PD in clinical settings and potentially prevent the disease from advancing to more severe stages.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.relation.isversionof10.1002/brb3.3395en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCognitive Impairmenten_US
dc.subjectDementiaen_US
dc.subjectfMRIen_US
dc.subjectMCIen_US
dc.subjectParkinson’s Diseaseen_US
dc.subjectResting-Stateen_US
dc.titleFunctional Neural Networks Stratify Parkinson’s Disease Patients Across the Spectrum of Cognitive Impairmenten_US
dc.typearticleen_US
dc.relation.journalBrain and Behavioren_US
dc.contributor.departmentFSM Vakıf Üniversitesi, Edebiyat Fakültesi, Psikoloji Bölümüen_US
dc.contributor.authorIDhttps://orcid.org/0000-0002-5286-4981en_US
dc.contributor.authorIDhttps://orcid.org/0000-0003-0552-8464en_US
dc.contributor.authorIDhttps://orcid.org/0000-0002-1289-4641en_US
dc.contributor.authorIDhttps://orcid.org/0000-0001-8563-5635en_US
dc.contributor.authorIDhttps://orcid.org/0000-0001-6238-2102en_US
dc.contributor.authorIDhttps://orcid.org/0000-0003-4292-5717en_US
dc.contributor.authorIDhttps://orcid.org/0000-0002-2752-1223en_US
dc.contributor.authorIDhttps://orcid.org/0000-0001-5118-4776en_US
dc.identifier.volume14en_US
dc.identifier.issue1en_US
dc.identifier.startpage1en_US
dc.identifier.endpage19en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorTemel, Zeynep


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