ArticleFrontiers in neuroscience2016
Multimodal Imaging Signatures of Parkinson's Disease.
Article in Frontiers in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Resting-State Functional Connectivity of Sensorimotor and Default Mode Networks and Lower Limb Performance in Chronic Stroke: A Cross-Sectional Study.Brain and behavior · 2025Article
- Cross-modal fusion of brain imaging and clinical data for Parkinson's disease progression prediction.PloS one · 2025Article
- Neural network localization in Parkinson's disease with impulse control disorders.Frontiers in aging neuroscience · 2025Article
- Multimodal magnetic resonance neuroimaging measures characteristic of early cART-treated pediatric HIV: A feature selection approach.Human brain mapping · 2022Article
- Analyzing Hierarchical Multi-View MRI Data With StaPLR: An Application to Alzheimer's Disease Classification.Frontiers in neuroscience · 2022Article
- High-Order Laplacian Regularized Low-Rank Representation for Multimodal Dementia Diagnosis.Frontiers in neuroscience · 2021Article
- Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation.An international journal on information fusion · 2020Article
- Integrating photoacoustic microscopy, optical coherence tomography, OCT angiography, and fluorescence microscopy for multimodal imaging.Experimental biology and medicine (Maywood, N.J.) · 2020Article
- Detecting and Testing Altered Brain Connectivity Networks with K-partite Network Topology.Computational statistics & data analysis · 2020Article
- Towards understanding neural network signatures of motor skill learning in Parkinson's disease and healthy aging.The British journal of radiology · 2019Review
- A totally data-driven whole-brain multimodal pipeline for the discrimination of Parkinson's disease, multiple system atrophy and healthy control.NeuroImage. Clinical · 2019Article
- A Bayesian Spatial Model to Predict Disease Status Using Imaging Data From Various Modalities.Frontiers in neuroscience · 2018Article
- A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.NeuroImage · 2017Article
- Progression marker of Parkinson's disease: a 4-year multi-site imaging study.Brain : a journal of neurology · 2017Article
- Diagnostic classification of unipolar depression based on resting-state functional connectivity MRI: effects of generalization to a diverse sample.Journal of neural transmission (Vienna, Austria : 1996) · 2017Article
- Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program.Biomarkers in medicine · 2017Article
- Complexity of resting-state EEG activity in the patients with early-stage Parkinson's disease.Cognitive neurodynamics · 2017Article
- Pattern of Reduced Functional Connectivity and Structural Abnormalities in Parkinson's Disease: An Exploratory Study.Frontiers in neurology · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disorder that manifests through hallmark motor symptoms, often accompanied by a range of non-motor symptoms. There is a putative delay between the onset of the neurodegenerative process, marked by the death of dopamine-producing cells, and the onset of motor symptoms, creating an urgent need to develop biomarkers that may yield early PD detection. Neuroimaging offers a non-invasive approach to examining the potential utility of a vast number of functional and structural brain characteristics as biomarkers. We present a statistical framework for analyzing neuroimaging data from multiple modalities to determine features that reliably distinguish PD patients from healthy control (HC) subjects. Our approach builds on elastic net, performing regularization and variable selection, while introducing additional criteria centering on parsimony and reproducibility. We apply our method to data from 42 subjects (28 PD patients and 14 HC). Our approach demonstrates extremely high accuracy, assessed via cross-validation, and isolates brain regions that are implicated in the neurodegenerative PD process.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.