ArticleNeurobiology of disease2023
Parkinsonian daytime sleep-wake classification using deep brain stimulation lead recordings.
Article in Neurobiology of disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Excessive daytime sleepiness in parkinsonism is associated with cortical and basal ganglia beta oscillatory activity.Communications biology · 2026Article
- The Impact of Deep Brain Stimulation of the Subthalamic Nucleus on Sleep-Wake Function and Circadian Rhythms in Patients with Parkinson's Disease.Movement disorders clinical practice · 2025Article
- Alterations in beta oscillatory activity occur with the emergence of parkinsonian motor signs across the basal ganglia-thalamocortical network.Neurobiology of disease · 2025Article
- Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine.CNS neuroscience & therapeutics · 2024Article
- Slow-wave sleep dysfunction in mild parkinsonism is associated with excessive beta and reduced delta oscillations in motor cortex.Frontiers in neuroscience · 2024Article
- Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop.Journal of neurology · 2023Review
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Excessive daytime sleepiness is a recognized non-motor symptom that adversely impacts the quality of life of people with Parkinson's disease (PD), yet effective treatment options remain limited. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for PD motor signs. Reliable daytime sleep-wake classification using local field potentials (LFPs) recorded from DBS leads implanted in STN can inform the development of closed-loop DBS approaches for prompt detection and disruption of sleep-related neural oscillations. We performed STN DBS lead recordings in three nonhuman primates rendered parkinsonian by administrating neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Reference sleep-wake states were determined on a second-by-second basis by video monitoring of eyes (eyes-open, wake and eyes-closed, sleep). The spectral power in delta (1-4 Hz), theta (4-8 Hz), low-beta (8-20 Hz), high-beta (20-35 Hz), gamma (35-90 Hz), and high-frequency (200-400 Hz) bands were extracted from each wake and sleep epochs for training (70% data) and testing (30% data) a support vector machines classifier for each subject independently. The spectral features yielded reasonable daytime sleep-wake classification (sensitivity: 90.68 ± 1.28; specificity: 88.16 ± 1.08; accuracy: 89.42 ± 0.68; positive predictive value; 88.70 ± 0.89, n = 3). Our findings support the plausibility of monitoring daytime sleep-wake states using DBS lead recordings. These results could have future clinical implications in informing the development of closed-loop DBS approaches for automatic detection and disruption of sleep-related neural oscillations in people with PD to promote wakefulness.
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