Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A dynamical-systems model for Parkinson's disease.

C I Connolly1, J B Burns, M S Jog

  • 1Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. connolly@ai.sri.com

Biological Cybernetics
|August 10, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Quantifying Brain Iron in Hereditary Hemochromatosis Using R2* and Susceptibility Mapping.

AJNR. American journal of neuroradiology·2022
Same author

The Effect of Single Accreditation on Medical Student Match Rates in Surgical Specialties.

Cureus·2021
Same author

Medication status and dual-tasking on turning strategies in Parkinson disease.

Journal of the neurological sciences·2018
Same author

Daclizumab phase II trial in relapsing and remitting multiple sclerosis: MRI and clinical results.

Neurology·2007
Same author

An evaluation of sensorimotor integration during locomotion toward a target in Parkinson's disease.

Neuroscience·2005
Same author

Tetrode technology: advances in implantable hardware, neuroimaging, and data analysis techniques.

Journal of neuroscience methods·2002
Same journal

Harmonic memory in phasor neural networks.

Biological cybernetics·2026
Same journal

Correction: Decreased spinal inhibition leads to undiversified locomotor patterns.

Biological cybernetics·2026
Same journal

Foundational issues of network models in biology.

Biological cybernetics·2026
Same journal

Dynamical mechanisms for coordinating long-term working memory based on the precision of spike-timing in cortical neurons.

Biological cybernetics·2026
Same journal

Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles.

Biological cybernetics·2026
Same journal

Fluctuation-response relations for a two-stage population of spiking neurons stimulated by common noise.

Biological cybernetics·2026
See all related articles

This study introduces a novel striatal model to explain Parkinson's disease (PD) motor symptoms. The model, using particle dynamics, successfully simulates normal movement and reproduces PD-related hypokinetic and hyperkinetic features.

Area of Science:

  • Computational neuroscience
  • Motor control systems
  • Neurodegenerative disease modeling

Background:

  • Parkinson's disease (PD) exhibits a complex mix of hypokinetic and hyperkinetic motor symptoms.
  • Existing models of the basal ganglia face challenges in replicating this symptom duality.
  • Understanding the striatum's role is crucial for modeling PD pathophysiology.

Purpose of the Study:

  • To propose and validate a computational model of the striatum capable of explaining the diverse motor symptoms in Parkinson's disease.
  • To provide a framework for understanding how striatal dysfunction contributes to PD motor deficits.
  • To utilize a physics-based approach to model motor planning and execution.

Main Methods:

  • Developed a computational model of the striatum based on particle dynamics within a potential energy landscape.

Related Experiment Videos

  • Modeled motor planning using Hamilton's equations, with potentials generated internally within striatal modules.
  • Validated the model through dynamic simulations of a two-link robot arm, comparing normal and PD-affected movement patterns.

    • Main Results:

    • The model successfully simulated normal movement, exhibiting experimentally observed properties.
    • Simulations reproduced key motor symptoms characteristic of Parkinson's disease, including both hypokinetic and hyperkinetic features.
    • The model demonstrated the potential impact of hypothetical PD-related pathologies on striatal function and motor output.

    Conclusions:

    • The proposed striatal model offers a unified explanation for the heterogeneous motor symptoms in Parkinson's disease.
    • This computational approach provides a valuable tool for investigating basal ganglia function and dysfunction in PD.
    • The findings highlight the utility of physics-inspired models in understanding complex neurological disorders.