Reciprocity Between the Cerebellum and the Cerebral Cortex: Nonlinear Dynamics in Microscopic Modules fop Generating Voluntary Motor Commands

Authored by William Rand, Jun Wang, Uri Wilensky, Gregory Dam, Sule Yildirim, James C. Houk

DOI: 10.1002/cplx.20241

Sponsors: United States National Institutes of Health (NIH)

Platforms: NetLogo

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

The cerebellum and basal ganglia are reciprocally connected with the cerebral cortex, forming many loops that function as distributed processing modules. Here we present a detailed model of one microscopic loop between the motor cortex and the cerebellum, and we show how small arrays of these microscopic loops (CB modules) can be used to generate biologically plausible motor commands for controlling movement. A fundamental feature of CB modules is the presence of positive feedback loops between the cerebellar nucleus and the motor cortex. We use nonlinear dynamics to model one microscopic loop and to investigate its bistable properties. Simulations demonstrate an ability to program a motor command well in advance of command generation and an ability to vary command duration. However, control of command intensity is minimal, which could interfere with the control of movement velocity. To assess these hypotheses, we use a minimal nonlinear model of the neuromuscular (NM) system that translates motor commands into actual movements. Simulations of the combined CB-NM modular model indicate that movement duration is readily controlled, whereas velocity is poorly controlled. We than explore how an array of eight CB-NM modules can be used to control the direction and endpoint of a planar movement. In actuality, thousands of such microscopic loops function together as an array of adjustable pattern generators for programming and regulating the composite motor commands that control limb movements. We discuss the biological plausibility and limitations of the model. We also discuss ways in which an agent-based representation can take advantage of the modularity in order to model this complex system. (C) 2008 Wiley Periodicals, Inc. Complexity 14: 29-45, 2008
Tags
Agent-based modeling movement Nonlinear dynamics cerebellum equilibrium point control motor command motor cortex neural network