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The neural mechanisms of risk aversion.

Fukunaga, Rena.

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The neural mechanisms of risk aversion.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The neural mechanisms of risk aversion./
Author:	Fukunaga, Rena.
Description:	218 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-01(E), Section: B.
Contained By:	Dissertation Abstracts International76-01B(E).
Subject:	Cognitive psychology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3635142
ISBN:	9781321161137

The neural mechanisms of risk aversion.
Fukunaga, Rena.

The neural mechanisms of risk aversion. - 218 p.

Source: Dissertation Abstracts International, Volume: 76-01(E), Section: B.

Thesis (Ph.D.)--Indiana University, 2014.

Increased risk taking behavior is a hallmark clinical feature in a wide range of psychiatric disorders that is typically associated with serious life-altering negative consequences. In contrast, individuals that effectively weigh the costs and benefits of possible outcomes are often able to avoid deleterious behaviors by making the "better" choice. To improve our understanding of the phenomenology of risk-taking behaviors in the context of complex decision making, a multitude of disciplines have turned their attention towards exploring the underlying cognitive mechanisms associated with the neurofunctional sequelae of risky behaviors. In the years to come, the gap between basic and applied sciences will most likely be narrowed as new insights gained from examining risk-related brain processes will be applied in the development of optimally targeted behavioral and physiological interventions designed to curtail a myriad of risk-taking behaviors.

ISBN: 9781321161137Subjects--Topical Terms:

523881
Cognitive psychology.

The neural mechanisms of risk aversion.
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245 1 4 $a The neural mechanisms of risk aversion.
300 $a 218 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-01(E), Section: B.
500 $a Adviser: Joshua W. Brown.
502 $a Thesis (Ph.D.)--Indiana University, 2014.
520 $a Increased risk taking behavior is a hallmark clinical feature in a wide range of psychiatric disorders that is typically associated with serious life-altering negative consequences. In contrast, individuals that effectively weigh the costs and benefits of possible outcomes are often able to avoid deleterious behaviors by making the "better" choice. To improve our understanding of the phenomenology of risk-taking behaviors in the context of complex decision making, a multitude of disciplines have turned their attention towards exploring the underlying cognitive mechanisms associated with the neurofunctional sequelae of risky behaviors. In the years to come, the gap between basic and applied sciences will most likely be narrowed as new insights gained from examining risk-related brain processes will be applied in the development of optimally targeted behavioral and physiological interventions designed to curtail a myriad of risk-taking behaviors.
520 $a Thus, the specific aim of this study is to clarify the brain mechanisms that assess the likely good and bad outcomes associated with risk-taking behaviors, and to explore how these mechanisms, in turn, can be manipulated to increase the avoidance of less-optimal behaviors. Research links regions of the anterior cingulate cortex (ACC) and anterior insula (AI), as well as cognitive processes involved in performance monitoring (especially error, conflict, and error likelihood effects), to risk avoidance (Brown & Braver, 2007). Yet, it remains unclear as to how the brain detects and avoids potentially harmful behavior, and why some individuals are better able to avoid risky behaviors. A series of fMRI decision-making tasks showed consistent activation patterns for how underlying risks of a particular action are represented in the brain. A separate neuroimaging study found such patterns of risk-related signals to be best accounted for by a formalism of risk conceived as the variance of the possible outcomes; distinct from other possible cognitive constructs such as loss probability and loss severity. Collectively, these findings are likely to provide new theoretical and methodological insights for conducting research involving risk-taking behaviors across a multitude of disciplines including the fields of behavioral decision theory, clinical science, and cognitive neuroscience.
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