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dc.contributor.authorSeeley, Corrine Jessieen
dc.date2015-05-26 09:37:41.621
dc.date.accessioned2015-05-26T13:58:03Z
dc.date.available2015-05-26T13:58:03Z
dc.date.issued2015-05-26
dc.identifier.urihttp://hdl.handle.net/1974/13088
dc.descriptionThesis (Ph.D, Neuroscience Studies) -- Queen's University, 2015-05-26 09:37:41.621en
dc.description.abstractThe Iowa Gambling Task (IGT) is a widely used decision-making task often used to assess decision-making impairment in clinical populations. During learning of the task, individuals receive consistent monetary rewards and inconsistent monetary punishments of different frequencies and magnitudes. Learning relies on in part the ventromedial prefrontal cortex (vmPFC) which integrates reward and loss information to identify the decks with the highest expected value (EV). Currently, little is known about factors that might influence this unique process. This thesis uses experimental techniques to investigate how sleep and punishment structures can influence learning of the IGT. In Chapter 2 we show evidence that a period of post-learning sleep enhances IGT learning, specifically via reduced choice from deck B. Deck B is an initially preferred “bad” deck that requires integrating a large infrequent $1250 punishment to discover its negative EV. In Chapter 3 we link this improvement to increased theta (4-8 Hz) activity in the vmPFC and left prefrontal cortex. We also show evidence that pre-sleep anticipatory emotions correlate to heightened theta activity in the right vmPFC during post acquisition REM. Finally, chapter 4 provides the first evidence that higher-order punishment structures can influence learning of the task. We provide the first evidence that punishment structures with high variance/skew may cause risk-aversion and that IGT decision-making may not be driven by EV alone. Collectively, the work presented provides much needed knowledge on factors that can influence IGT learning. We are the first to show evidence that IGT learning may be enhanced with post learning REM sleep and suggest that similar areas that are involved in online learning (i.e., vmPFC) may be involved. We are also the first to show that performance can be influenced by higher-order punishment structures. Taken together, this body of work reveals that integrating punishments into value estimates may be enhanced by post learning REM sleep and influenced by higher-order punishment structures. These results have widespread implications for how punishment structures in our day-to-day life may influence online and offline decision processes and provides a strong foundation for continued work to understand decision-making in healthy and clinical groups.en
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsCreative Commons - Attribution - CC BYen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectNeuroeconomicsen
dc.subjectSleepen
dc.subjectSkewen
dc.subjectDecision-Makingen
dc.subjectIowa Gambling Tasken
dc.subjectREM Sleepen
dc.subjectvmPFCen
dc.subjectVarianceen
dc.titleRapid Eye Movement Sleep, Punishment Structure and Decision-Making of the Iowa Gambling Tasken
dc.typethesisen
dc.description.degreePhDen
dc.contributor.supervisorBeninger, Richard J.en
dc.contributor.supervisorSmith, Carlyle T.en
dc.contributor.departmentNeuroscience Studiesen
dc.degree.grantorQueen's University at Kingstonen


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