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Updated: Aug 10, 2026

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
Published on: January 7, 2014
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
Abstract:
The juxtaposition of hypokinetic and hyperkinetic symptoms in Parkinson's disease (PD) presents a challenge in modeling the basal ganglia. We propose a model of the striatum that can account for the mixture of symptoms seen in PD. In the model, the problem of motor planning is cast in terms of a particle in a potential, where potentials are generated internally in striatal modules, subject to afferent control. Planned movement is governed by Hamilton's equations, where potential energy is supplied by potentials expressed in the striatum. To test the model in realistic situations, a dynamic simulation of a two-link robot arm was used. Normal movement is modeled and shown to exhibit observed experimental properties. Symptoms of PD are reproduced by modeling hypothetical consequences of PD pathology.
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