ArticleBrain : a journal of neurology2020
Subthalamic nucleus activity dynamics and limb movement prediction in Parkinson's disease.
Article in Brain : a journal of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Spatial propagation of movement-related basal ganglia activity predicts parkinsonian motor state.Brain : a journal of neurology · 2026Article
- Decoding pre-movement neural activity from thalamic LFPs for adaptive neurostimulation in tremor patients.Neurocomputing · 2026Article
- Computational Modeling of Parkinson's Disease Across Scales: From Mechanisms to Biomarkers, Drug Discovery, and Personalized Therapies.Brain sciences · 2026Review
- Cerebellar motor and non-motor contributions to dystonia pathophysiology and treatment.Dystonia (Lausanne, Switzerland) · 2026Article
- Transformer-based long-term predictor of subthalamic beta activity in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Bimanual coordination and neuromuscular synchronization in Parkinson's disease and healthy adults.Experimental brain research · 2025Article
- Subthalamic stimulation modulates context-dependent effects of beta bursts during fine motor control.Nature communications · 2024Article
- Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease.NPJ Parkinson's disease · 2024Article
- Structural covariance alterations reveal motor damage in periventricular leukomalacia.Brain communications · 2024Article
- Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop.Journal of neurology · 2023Review
- Wavelet-Based Bracketing, Time-Frequency Beta Burst Detection: New Insights in Parkinson's Disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023Article
- Landscape and future directions of machine learning applications in closed-loop brain stimulation.NPJ digital medicine · 2023Review
- When do bursts matter in the primary motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states.Progress in neurobiology · 2023Article
- Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease.Neuromodulation : journal of the International Neuromodulation Society · 2023Article
- Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives.Journal of Parkinson's disease · 2023Review
- Progress in the development of a fully implantable brain-computer interface: the potential of sensing-enabled neurostimulators.National science review · 2022Article
- Article
- Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation.Experimental neurology · 2022Review
- The exploration of Parkinson's disease: a multi-modal data analysis of resting functional magnetic resonance imaging and gene data.Brain imaging and behavior · 2021Article
- Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson's disease.PLoS computational biology · 2021Article
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Authors and funding
13 authors.
Funding
Abstract
Whilst exaggerated bursts of beta frequency band oscillatory synchronization in the subthalamic nucleus have been associated with motor impairment in Parkinson's disease, a plausible mechanism linking the two phenomena has been lacking. Here we test the hypothesis that increased synchronization denoted by beta bursting might compromise information coding capacity in basal ganglia networks. To this end we recorded local field potential activity in the subthalamic nucleus of 18 patients with Parkinson's disease as they executed cued upper and lower limb movements. We used the accuracy of local field potential-based classification of the limb to be moved on each trial as an index of the information held by the system with respect to intended action. Machine learning using the naïve Bayes conditional probability model was used for classification. Local field potential dynamics allowed accurate prediction of intended movements well ahead of their execution, with an area under the receiver operator characteristic curve of 0.80 ± 0.04 before imperative cues when the demanded action was known ahead of time. The presence of bursts of local field potential activity in the alpha, and even more so, in the beta frequency band significantly compromised the prediction of the limb to be moved. We conclude that low frequency bursts, particularly those in the beta band, restrict the capacity of the basal ganglia system to encode physiologically relevant information about intended actions. The current findings are also important as they suggest that local subthalamic activity may potentially be decoded to enable effector selection, in addition to force control in restorative brain-machine interface applications.
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