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Neuroeconomic Studies on Personality and Decision-Making.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Neuroeconomic Studies on Personality and Decision-Making./
作者:	Hawes, Daniel Rohan.
面頁冊數:	1 online resource (84 pages)
附註:	Source: Dissertation Abstracts International, Volume: 75-11(E), Section: A.
標題:	Economic theory. -
電子資源:	click for full text (PQDT)
ISBN:	9781321086416

Neuroeconomic Studies on Personality and Decision-Making.
Hawes, Daniel Rohan.

Neuroeconomic Studies on Personality and Decision-Making. - 1 online resource (84 pages)

Source: Dissertation Abstracts International, Volume: 75-11(E), Section: A.

Thesis (Ph.D.)--University of Minnesota, 2013.

Includes bibliographical references

Neural activity causally underlies human cognition and behavior. Investigating the neurobiological principles and computational mechanisms governing brain activity during decision-making provides a way to improve theories of human behavior in the natural as well as social sciences (Glimcher & Rustichini 2004; Rustichini, 2009; Fehr & Rangel, 2009). In this context, the discipline of Neuroeconomics was originally conceived as an endeavor to interrogate neural activity during economic decision-making with the aim of evaluating competing decision theories (Rustichini, 2008; Glimcher, Camerer, Fehr & Poldrack 2009). From this origin, Neuroeconomics has evolved into a full-fledged enterprise of consilience; an attempt to not only test and bridge, but truly unify natural science and social science explanations of human behavior (Wilson, 1998; Glimcher & Rustichini, 2004; Rangel, Camerer & Montague, 2008).

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781321086416Subjects--Topical Terms:

809881
Economic theory.
Index Terms--Genre/Form:

554714
Electronic books.

Neuroeconomic Studies on Personality and Decision-Making.
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100 1 $a Hawes, Daniel Rohan. $3 1186703
245 1 0 $a Neuroeconomic Studies on Personality and Decision-Making.
264 0 $c 2013
300 $a 1 online resource (84 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Dissertation Abstracts International, Volume: 75-11(E), Section: A.
500 $a Advisers: Aldo Rustichini; Terrance Hurley.
502 $a Thesis (Ph.D.)--University of Minnesota, 2013.
504 $a Includes bibliographical references
520 $a Neural activity causally underlies human cognition and behavior. Investigating the neurobiological principles and computational mechanisms governing brain activity during decision-making provides a way to improve theories of human behavior in the natural as well as social sciences (Glimcher & Rustichini 2004; Rustichini, 2009; Fehr & Rangel, 2009). In this context, the discipline of Neuroeconomics was originally conceived as an endeavor to interrogate neural activity during economic decision-making with the aim of evaluating competing decision theories (Rustichini, 2008; Glimcher, Camerer, Fehr & Poldrack 2009). From this origin, Neuroeconomics has evolved into a full-fledged enterprise of consilience; an attempt to not only test and bridge, but truly unify natural science and social science explanations of human behavior (Wilson, 1998; Glimcher & Rustichini, 2004; Rangel, Camerer & Montague, 2008).
520 $a This dissertation binds two neuroeconomic studies of decision-making with an introduction and concluding commentary. The introduction presents a brief introduction to Neuroeconomics, meant to locate both research studies in the existing literature and philosophy of this field. The conclusion provides a brief appraisal of the role of Neuroeconomics in further advancing the kind of research into decision-making reported here.
520 $a Both studies in this dissertation comprise investigations of human behavior during experience-based decision-making, with a special focus on the fundamental value computations that underlie such choice behavior.
520 $a Study 1 investigates the role of neural reinforcement signals during learning of a strategic decision task from experience.
520 $a Study 2 investigates the moderating effect of intelligence on neural reinforcement signals during a sequential binary choice task.
520 $a Study 1 is reproduced from (Hawes, Vostroknutov & Rustichini 2013), and study 2 is reproduced from (Hawes, DeYoung, Gray & Rustichini; under review).
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Economic theory. $3 809881
650 4 $a Cognitive psychology. $3 556029
650 4 $a Neurosciences. $3 593561
650 4 $a Personality psychology. $3 1180475
655 7 $a Electronic books. $2 local $3 554714
690 $a 0511
690 $a 0633
690 $a 0317
690 $a 0625
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Minnesota. $b Applied Economics. $3 1179137
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3630610 $z click for full text (PQDT)