Geometric Structure of the Adaptive Controller of the Human Arm

Abstract

The objects with which the hand interacts with may significantly change the dynamics of the arm. How does the brain adapt control of arm movements to this new dynamics? We show that adaptation is via composition of a model of the task's dynamics. By exploring generalization capabilities of this adaptation we infer some of the properties of the computational elements with which the brain formed this model: the elements have broad receptive fields and encode the teamed dynamics as a map structured in an intrinsic coordinate system closely related to the geometry of the skeletomusculature. The low--level nature of these elements suggests that they may represent a set of primitives with which a movement is represented in the CNS.

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Document Details

Document Type
Technical Report
Publication Date
Jul 21, 1993
Accession Number
ADA276797

Entities

People

  • Ferdinando Mussa-ivaldi
  • Reza Shadmehr

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Brain
  • Cognitive Science
  • Computational Science
  • Control Systems
  • Coordinate Systems
  • Dynamics
  • Environment
  • Geometry
  • Learning
  • Mathematical Models
  • Mechanical Engineering
  • Mechanical Properties
  • Nervous System
  • Neurosciences
  • Psychology
  • Simulations

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms