NOCH: A framework for biologically plausible models of neural motor control
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...
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ndltd-LACETR-oai-collectionscanada.gc.ca-OWTU.10012-49492013-10-04T04:09:40ZDeWolf, 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 |
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en |
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Motor control control theory neural motor control optimal hierarchical Computer Science |
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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_ |
1716600343335272448 |