ArticleJournal of neurophysiology2020
Prediction of mild parkinsonism revealed by neural oscillatory changes and machine learning.
Article in Journal of neurophysiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Parkinsonism disrupts the population-level organization of cortical dynamics.bioRxiv : the preprint server for biology · 2026Article
- Alterations in beta oscillatory activity occur with the emergence of parkinsonian motor signs across the basal ganglia-thalamocortical network.Neurobiology of disease · 2025Article
- Transient Increases in Neural Oscillations and Motor Deficits in a Mouse Model of Parkinson's Disease.International journal of molecular sciences · 2024Article
- Parkinsonian daytime sleep-wake classification using deep brain stimulation lead recordings.Neurobiology of disease · 2023Article
- Consistent Changes in Cortico-Subthalamic Directed Connectivity Are Associated With the Induction of Parkinsonism in a Chronically Recorded Non-human Primate Model.Frontiers in neuroscience · 2022Article
- Long-lasting effects of subthalamic nucleus coordinated reset deep brain stimulation in the non-human primate model of parkinsonism: A case report.Brain stimulationArticle
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Neural oscillatory changes within and across different frequency bands are thought to underlie motor dysfunction in Parkinson's disease (PD) and may serve as biomarkers for closed-loop deep brain stimulation (DBS) approaches. Here, we used neural oscillatory signals derived from chronically implanted cortical and subcortical electrode arrays as features to train machine learning algorithms to discriminate between naive and mild PD states in a nonhuman primate model. Local field potential (LFP) data were collected over several months from a 12-channel subdural electrocorticography (ECoG) grid and a 6-channel custom array implanted in the subthalamic nucleus (STN). Relative to the naive state, the PD state showed elevated primary motor cortex (M1) and STN power in the beta, high gamma, and high-frequency oscillation (HFO) bands and decreased power in the delta band. Theta power was found to be decreased in STN but not M1. In the PD state there was elevated beta-HFO phase-amplitude coupling (PAC) in the STN. We applied machine learning with support vector machines with radial basis function (SVM-RBF) kernel and
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