ArticleNeuroImage. Clinical2019
Cerebellar resting-state functional connectivity in Parkinson's disease and multiple system atrophy: Characterization of abnormalities and potential for differential diagnosis at the single-patient level.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Altered regional spontaneous brain activity in Parkinson's disease: a meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- Machine Learning for the Diagnosis of Parkinson's Disease: A Review of Literature.Frontiers in aging neuroscience · 2021Pooled it
- Functional brain abnormalities in post COVID-19 condition and their relationship with cognition.Scientific reports · 2025Trial
- Mapping the Disrupted Connectome in Spinocerebellar Ataxia Type 3: A Network-Based Statistics Study Identifying Novel Therapeutic Targets for Neuromodulation.CNS neuroscience & therapeutics · 2026Article
- Functional MRI in Multiple System Atrophy: A Promising Biomarker for Clinical Applications.Neuropsychiatric disease and treatment · 2026Review
- Discriminative compensatory activation during auditory beat perception in Parkinson's disease and multiple system atrophy.Frontiers in neuroscience · 2026Article
- Regional homogeneity differences in resting-state fMRI between Parkinson's disease and multiple system atrophy-parkinsonian type.Journal of neural transmission (Vienna, Austria : 1996) · 2026Article
- Novel applications of machine learning and computational neuroscience models to neuroimaging in Parkinson's disease and related disorders.Frontiers in aging neuroscience · 2026Review
- Hierarchical reorganization of cortical and cerebellar functional gradients in Parkinson's disease.Frontiers in neurology · 2026Article
- Brain structural features with functional priori to classify Parkinson's disease and multiple system atrophy using diagnostic MRI.Scientific reports · 2025Article
- Investigating resting-state functional connectivity changes within procedural memory network across neuropsychiatric disorders using fMRI.BMC medical imaging · 2025Article
- Resting-State Functional MRI Approaches to Parkinsonisms and Related Dementia.Current neurology and neuroscience reports · 2024Review
- Iron deposition is associated with motor and non-motor network breakdown in parkinsonism.Frontiers in aging neuroscience · 2024Article
- Network disruption based on multi-modal EEG-MRI in α-synucleinopathies.Frontiers in neurology · 2024Article
- Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?Current neuropharmacology · 2024Review
- Multi-parametric radiomics of conventional T1 weighted and susceptibility-weighted imaging for differential diagnosis of idiopathic Parkinson's disease and multiple system atrophy.BMC medical imaging · 2023Article
- How should we be using biomarkers in trials of disease modification in Parkinson's disease?Brain : a journal of neurology · 2023Article
- Linking the cerebellum to Parkinson disease: an update.Nature reviews. Neurology · 2023Review
- Elevated Levels of Serum Biomarkers Associated with Damage to the CNS Neurons and Endothelial Cells Are Linked with Changes in Brain Connectivity in Breast Cancer Patients with Vestibulo-Atactic Syndrome.Pathophysiology : the official journal of the International Society for Pathophysiology · 2023Article
- Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages.Human brain mapping · 2023Article
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11 authors.
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Abstract
backgroundRecent studies using resting-state functional connectivity and machine-learning to distinguish patients with neurodegenerative diseases from other groups of subjects show promising results. This approach has not been tested to discriminate between Parkinson's disease (PD) and multiple system atrophy (MSA) patients.
objectivesOur first aim is to characterize possible abnormalities in resting-state functional connectivity between the cerebellum and a set of intrinsic-connectivity brain networks and between the cerebellum and different regions of the striatum in PD and MSA. The second objective of this study is to assess the potential of cerebellar connectivity measures to distinguish between PD and MSA patients at the single-patient level.
methodsFifty-nine healthy controls, 62 PD patients, and 30 MSA patients underwent resting-state functional MRI with a 3T scanner. Independent component analysis and dual regression were used to define seven resting-state networks of interest. To assess striatal connectivity, a seed-to-voxel approach was used after dividing the striatum into six regions bilaterally. Measures of cerebellar-brain network and cerebellar-striatal connectivity were then used as features in a support vector machine to discriminate between PD and MSA patients.
resultsMSA patients displayed reduced cerebellar connectivity with different brain networks and with the striatum compared with PD patients and with controls. The classification procedure achieved an overall accuracy of 77.17% with 83.33% of the MSA subjects and 74.19% of the PD patients correctly classified.
conclusionOur findings suggest that measures of cerebellar functional connectivity have the potential to distinguish between PD and MSA patients.
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