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Open AccessJournal ArticleDOI

A framework for studying the neurobiology of value-based decision making

TLDR
A framework to investigate different aspects of the neurobiology of decision making is proposed to bring together recent findings in the field, highlight some of the most important outstanding problems, define a common lexicon that bridges the different disciplines that inform neuroeconomics, and point the way to future applications.
Abstract
Neuroeconomics is the study of the neurobiological and computational basis of value-based decision making. Its goal is to provide a biologically based account of human behaviour that can be applied in both the natural and the social sciences. This Review proposes a framework to investigate different aspects of the neurobiology of decision making. The framework allows us to bring together recent findings in the field, highlight some of the most important outstanding problems, define a common lexicon that bridges the different disciplines that inform neuroeconomics, and point the way to future applications.

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Citations
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Neuroscience 細胞死:最近の知見

廣瀬雄一
TL;DR: In this paper, the authors describe a scenario where a group of people are attempting to find a solution to the problem of "finding the needle in a haystack" in the environment.
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Large-scale brain networks and psychopathology: a unifying triple network model

TL;DR: A triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology is proposed, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders.
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Emotion Regulation: Current Status and Future Prospects

TL;DR: A review of the current status and future prospects of the field of emotion regulation can be found in this paper, where the authors define emotion and emotion regulation and distinguish both from related constructs.
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Functional imaging studies of emotion regulation: a synthetic review and evolving model of the cognitive control of emotion.

TL;DR: This paper outlines a model of the processes and neural systems involved in emotion generation and regulation and shows how the model can be generalized to understand the brain mechanisms underlying other emotion regulation strategies as well as a range of other allied phenomena.
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Model-based influences on humans' choices and striatal prediction errors.

TL;DR: A multistep decision task designed to challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.
References
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Book

Reinforcement Learning: An Introduction

TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Book ChapterDOI

Prospect theory: an analysis of decision under risk

TL;DR: In this paper, the authors present a critique of expected utility theory as a descriptive model of decision making under risk, and develop an alternative model, called prospect theory, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights.
Journal ArticleDOI

Advances in prospect theory: cumulative representation of uncertainty

TL;DR: Cumulative prospect theory as discussed by the authors applies to uncertain as well as to risky prospects with any number of outcomes, and it allows different weighting functions for gains and for losses, and two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting function.
Journal ArticleDOI

An integrative theory of prefrontal cortex function

TL;DR: It is proposed that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them, which provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task.
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