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Patients with PD hypothetically progress from stages without CI (PD\u2010normal cognition [NC]) to stages with Mild CI (PD\u2010MCI) and PD dementia (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\u2010state functional connectivity (FC) among three CI stages of PD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We enrolled 88 patients with PD and 26 healthy controls (HC) for a cross sectional clinical study and performed intra\u2010 and inter\u2010network FC analysis in conjunction with comprehensive clinical cognitive assessment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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\u2013intra\u2010network FC in differentiating between PD\u2010MCI and PDD. Additionally, our results showed the importance of sensory motor network, VN, DMN, and salience network (SN) in the discriminating PD\u2010NC 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We propose that resting\u2010state networks (RSN) can be a discriminating factor in distinguishing the CI stages of PD and progressing from PD\u2010NC to MCI 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/brb3.3395","type":"journal-article","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T02:04:03Z","timestamp":1706148243000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Functional neural networks stratify Parkinson's disease patients across the spectrum of cognitive impairment"],"prefix":"10.1002","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5286-4981","authenticated-orcid":false,"given":"Farzin","family":"Hajebrahimi","sequence":"first","affiliation":[{"name":"Functional Imaging and Cognitive\u2010Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA) Istanbul Medipol University  Istanbul 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