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Reciprocity between the cerebellum and the cerebral cortex: Nonlinear dynamics in microscopic modules for generating voluntary motor commands
Authors:Jun Wang  Gregory Dam  Sule Yildirim  William Rand  Uri Wilensky  James C Houk
Institution:1. Department of Physiology, Northwestern University Medical School, Chicago, Illinois;2. Northwestern University Institute for Neuroscience, Chicago, Illinois;3. Department of Computer Science, Hedmark University College, Elverum, Norway;4. Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois;5. Center for Connected Learning and Computer‐Based Modeling, Northwestern University, Evanston, Illinois
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 then 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. © 2008 Wiley Periodicals, Inc. Complexity, 2008
Keywords:neural network  motor cortex  cerebellum  movement  nonlinear dynamics  motor command  equilibrium point control  agent‐based modeling
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