NOCH: A framework for biologically plausible models of neural motor control

Master's Thesis, 2010

Travis DeWolf

Abstract

This thesis examines the neurobiological components of the motor control system and relates it to current control theory in order to develop a novel framework for models of motor control in the brain. The presented framework is called the Neural Optimal Control Hierarchy (NOCH). A method of accounting for low level system dynamics with a Linear Bellman Controller (LBC) on top of a hierarchy is presented, as well as a dynamic scaling technique for LBCs that drastically reduces the computational power and storage requirements of the system. These contributions to LBC theory allow for low cost, high-precision control of movements in large environments without exceeding the biological constraints of the motor control system.

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Thesis

School
University of Waterloo
Address
Waterloo, ON
Volume
Masters of Mathematics
Type
Masters Thesis

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