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Multiple Perspectives on Decision Making

Multiple Perspectives on Decision Making
决策的多种视角
批准号:
6837427
负责人:
George R Mangun
金额:
$2.5万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-04-01 至 2005-06-30

项目摘要

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): The goal of the proposed conference is to bring together researchers from various disciplines to discuss a common topic: how we make decisions and carry them out. Decision-making is central to human cognition, and as such is of interest both to those who strive to understand how the brain subserves the mind, as well as to those who strive to understand how the choices that we make impact our societal and economic infrastructure - and vice versa. Ultimately, understanding the capacity of healthy individuals to make decisions will be of critical importance for understanding how this capacity fails in substance abuse and a variety of neurological disorders. The confirmed speakers for this conference will be presenting research and theories from the various perspectives of psychology, cognitive and systems neuroscience, economics, management, and political science. A key goal of this conference is to foster cross-fertilization between these different perspectives in order to generate novel questions and insights into decision-making. The speakers will describe work from the neuronal level to the behavioral level in the developing organism and the adult. Data will be presented both from healthy individuals and drug abusers.
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会议论文
NEURAL MECHANISM OF ATTENTIONAL CONTROL AND SELECTION
NEURAL MECHANISM OF ATTENTIONAL CONTROL AND SELECTION
  • 批准号:
    6230050
  • 项目类别:
  • 资助金额:
    $11.74万
  • 财政年份:
    2001
  • 负责人:
    George R Mangun
  • 依托单位:
NEURAL MECHANISM OF ATTENTIONAL CONTROL AND SELECTION
  • 批准号:
    6499218
  • 项目类别:
  • 资助金额:
    $11.74万
  • 财政年份:
    2001
  • 负责人:
    George R Mangun
  • 依托单位:
NEURAL MECHANISM OF ATTENTIONAL CONTROL AND SELECTION
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis