ArticleJournal of computational neuroscience2014
Origins and suppression of oscillations in a computational model of Parkinson's disease.
Article in Journal of computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 72 citations in OpenAlex.
- Modeling nonlinear oscillator networks using physics-informed hybrid reservoir computing.Scientific reports · 2025Article
- Pallidal Deep Brain Stimulation Enhances Habitual Behavior in a Neuro-Computational Basal Ganglia Model During a Reward Reversal Learning Task.The European journal of neuroscience · 2025Article
- Multiple time delay induced Hopf bifurcation of a cortex - basal ganglia model for Parkinson's Disease.Cognitive neurodynamics · 2024Article
- Suppression of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model.Journal of biological physics · 2023Article
- Dopamine depletion leads to pathological synchronization of distinct basal ganglia loops in the beta band.PLoS computational biology · 2023Article
- Closing the loop of DBS using the beta oscillations in cortex.Cognitive neurodynamics · 2021Article
- Leveraging deep learning to control neural oscillators.Biological cybernetics · 2021Article
- Interaction of Indirect and Hyperdirect Pathways on Synchrony and Tremor-Related Oscillation in the Basal Ganglia.Neural plasticity · 2021Article
- Optimal open-loop desynchronization of neural oscillator populations.Journal of mathematical biology · 2020Article
- The beta oscillation conditions in a simplified basal ganglia network.Cognitive neurodynamics · 2019Article
- Model-Based Evaluation of Closed-Loop Deep Brain Stimulation Controller to Adapt to Dynamic Changes in Reference Signal.Frontiers in neuroscience · 2019Article
- Different Dopaminergic Dysfunctions Underlying Parkinsonian Akinesia and Tremor.Frontiers in neuroscience · 2019Article
- Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson's disease.PLoS computational biology · 2018Article
- Systems approaches to optimizing deep brain stimulation therapies in Parkinson's disease.Wiley interdisciplinary reviews. Systems biology and medicine · 2018Review
- Pallidal Deep-Brain Stimulation Disrupts Pallidal Beta Oscillations and Coherence with Primary Motor Cortex in Parkinson's Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
- Article
- A Population of Indirect Pathway Striatal Projection Neurons Is Selectively Entrained to Parkinsonian Beta Oscillations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017Article
- Article
- A Consistent Definition of Phase Resetting Using Hilbert Transform.International scholarly research notices · 2017Article
- Using Biophysical Models to Understand the Effect of tDCS on Neurorehabilitation: Searching for Optimal Covariates to Enhance Poststroke Recovery.Frontiers in neurology · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
Efficacy of deep brain stimulation (DBS) for motor signs of Parkinson's disease (PD) depends in part on post-operative programming of stimulus parameters. There is a need for a systematic approach to tuning parameters based on patient physiology. We used a physiologically realistic computational model of the basal ganglia network to investigate the emergence of a 34 Hz oscillation in the PD state and its optimal suppression with DBS. Discrete time transfer functions were fit to post-stimulus time histograms (PSTHs) collected in open-loop, by simulating the pharmacological block of synaptic connections, to describe the behavior of the basal ganglia nuclei. These functions were then connected to create a mean-field model of the closed-loop system, which was analyzed to determine the origin of the emergent 34 Hz pathological oscillation. This analysis determined that the oscillation could emerge from the coupling between the globus pallidus external (GPe) and subthalamic nucleus (STN). When coupled, the two resonate with each other in the PD state but not in the healthy state. By characterizing how this oscillation is affected by subthreshold DBS pulses, we hypothesize that it is possible to predict stimulus frequencies capable of suppressing this oscillation. To characterize the response to the stimulus, we developed a new method for estimating phase response curves (PRCs) from population data. Using the population PRC we were able to predict frequencies that enhance and suppress the 34 Hz pathological oscillation. This provides a systematic approach to tuning DBS frequencies and could enable closed-loop tuning of stimulation parameters.
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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.