Reinforcement Learning and the Error -Related Negativity: A Computational and Neurophysiological Investigation
Holroyd, Clay Brian
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/82547
Description
Title
Reinforcement Learning and the Error -Related Negativity: A Computational and Neurophysiological Investigation
Author(s)
Holroyd, Clay Brian
Issue Date
2001
Doctoral Committee Chair(s)
Coles, Michael G.H.
Department of Study
Neuroscience
Discipline
Neuroscience
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Psychology, Psychobiology
Language
eng
Abstract
"This thesis presents a unified account of two neural systems concerned with the development and expression of adaptive behaviors: a mesencephalic dopamine system for reinforcement learning, and a ""generic"" error-processing system associated with anterior cingulate cortex. The existence of the error-processing system has been inferred from the ""Error-Related Negativity,"" a component of the event-related brain potential elicited when human subjects commit errors in reaction-time tasks. It is proposed that the Error-Related Negativity is generated when a negative reinforcement learning signal is conveyed to anterior cingulate cortex via the mesencephalic dopamine system, and that this signal is utilized by anterior cingulate cortex to modify performance on the task at hand. Support for this proposal is provided using both computational modelling and psychophysiological experimentation."
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.