Evidence map›Paper›PMID 40485236›Full record

ArticleCNS neuroscience & therapeutics2025

Clinical and Functional Connectivity Markers in Prediction of Hallucinations in Parkinson's Disease.

Guanglu Li, Mengxue Jiang, Xin Chen, Panpan Hu, Jun Liu, Kai Wang

Abstract readMulticenter Study
In one paragraph

Article in CNS neuroscience & therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Guanglu LiDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.ORCID 0000-0003-0368-8755
Mengxue JiangDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Xin ChenDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Panpan HuDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Jun LiuDepartment of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Kai WangDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsLongitudinal studies addressing the predictive value of brain network connectivity in PD hallucinations are lacking. This study investigated whether functional connectivity markers could predict PD hallucinations independently of clinical markers.

methodsThis study used data from the Parkinson's Progression Marker Initiative, a longitudinal multicenter study that aims to identify biomarkers of PD progression. One hundred and three newly diagnosed PD patients (mean age 63.10 ± 9.70 years, 65 males) underwent clinical assessments and functional MRI scanning at baseline. Independent component analysis was used to explore intra-network and inter-network functional connectivity differences between PD patients who developed hallucinations and those who did not during the 2-year follow-up.

resultsTwenty patients developed hallucinations during the follow-up. At baseline, significantly decreased connectivity within the dorsal attention network (t = -6.65 ~ -4.90, p < 0.05, FWE corrected) and increased connectivity within the default mode network (t = 6.16 ~ 7.78, p < 0.05, FWE corrected) were detected in PD patients who developed hallucinations compared to those who did not. Additionally, PD patients with hallucinations exhibited significantly decreased functional connectivity between the dorsal attention network and the visual network at baseline (t = -3.31, p = 0.02, FWE corrected). Binary regression analysis revealed that significant predictors of PD hallucinations included the presence of EDS (OR = 6.928, p = 0.022), the presence of autonomic dysfunction (OR = 6.531, p = 0.012), FC within the DMN (OR = 5.587, p = 0.006), FC within the DAN (OR = 0.217, p = 0.041), and FC between the DAN and VIS (OR = 0.004, p = 0.019) at baseline.

conclusionsThe findings provide evidence that disrupted brain network connectivity is associated with a greater risk of future hallucinations in PD. This may aid in the early identification of PD patients at risk of hallucinations and provide a basis for the development of new therapies.

Indexed as

BrainHallucinationsNerve NetParkinson DiseaseAgedDisease ProgressionFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle Ageddefault mode networkdorsal attention networkfunctional connectivityhallucinationsindependent component analysisParkinson's disease

Identifiers

PMID40485236
PMCPMC12146587

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