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

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

Show other versions (1)

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 accounti...

Full description

Bibliographic Details
Main Author: DeWolf, Travis
Language:en
Published: 2010
Subjects:
Motor control
control theory
neural motor control
optimal
hierarchical
Computer Science
Online Access:http://hdl.handle.net/10012/4949
id ndltd-WATERLOO-oai-uwspace.uwaterloo.ca-10012-4949
record_format oai_dc
spelling ndltd-WATERLOO-oai-uwspace.uwaterloo.ca-10012-49492013-01-08T18:53:02ZDeWolf, Travis2010-01-20T20:59:38Z2010-01-20T20:59:38Z2010-01-20T20:59:38Z2010-01-13http://hdl.handle.net/10012/4949This 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.enMotor controlcontrol theoryneural motor controloptimalhierarchicalNOCH: A framework for biologically plausible models of neural motor controlThesis or DissertationSchool of Computer ScienceMaster of MathematicsComputer Science
collection NDLTD
language en
sources NDLTD
topic Motor control
control theory
neural motor control
optimal
hierarchical
Computer Science
spellingShingle Motor control
control theory
neural motor control
optimal
hierarchical
Computer Science
DeWolf, Travis
NOCH: A framework for biologically plausible models of neural motor control
description 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.
author DeWolf, Travis
author_facet DeWolf, Travis
author_sort DeWolf, Travis
title NOCH: A framework for biologically plausible models of neural motor control
title_short NOCH: A framework for biologically plausible models of neural motor control
title_full NOCH: A framework for biologically plausible models of neural motor control
title_fullStr NOCH: A framework for biologically plausible models of neural motor control
title_full_unstemmed NOCH: A framework for biologically plausible models of neural motor control
title_sort noch: a framework for biologically plausible models of neural motor control
publishDate 2010
url http://hdl.handle.net/10012/4949
work_keys_str_mv AT dewolftravis nochaframeworkforbiologicallyplausiblemodelsofneuralmotorcontrol
_version_ 1716573481029599232

Similar Items