The covert expectation of reward during deliberation

深思熟虑过程中对奖励的隐秘期望

基本信息

  • 批准号:
    8653350
  • 负责人:
  • 金额:
    $ 7.3万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-02-01 至 2017-01-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Deliberation entails the serial examination and evaluation of outcomes. While there are detailed, mechanistic, and quantitative theories of non-deliberative decision-making, such theories of deliberative decision-making are still lacking. This is due to a lack of key experimental knowledge of the mechanisms of deliberation. Deliberative decision-making entails the sequential consideration of possibilities, requiring three steps in a repeated cycle: (1) prediction of the consequences of one's actions, (2) evaluation of those predicted consequences, and (3) selection of the best action. An important difficulty that has limited our ability to study deliberative decision-making is that the process of deliberation is covert, that is, the transient information being considered is not reflected in immediate behavior. However, new mathematical techniques now allow decoding of represented variables from neural ensembles at very fast timescales, enabling the observation of those transient, covert processes. The goal of this proposal is to track the covert prediction of reward outcomes as alternatives are evaluated. We have preliminary data that structures known to be involved in motivation and evaluation (ventral striatum, orbitofrontal cortex) show a transient activation of reward-related activity at certain deliberative decision-points. Combining newly available multi-structure recording techniques, newly developed tasks, newly improved neural ensemble analysis techniques, and computational modeling, we will examine the relationship between the representations of future possibilities in hippocampus and the covert reappearance of reward-related information in structures known to be involved in motivation and reward and decision-making.
描述(由申请人提供):审议需要对结果进行系列检查和评价。虽然有详细的,机械的,定量的非审议决策理论,这样的审议决策理论仍然缺乏。这是由于缺乏对审议机制的关键实验知识。深思熟虑的决策需要对各种可能性进行连续的考虑,在一个重复的周期中需要三个步骤:(1)预测自己行动的后果,(2)评估这些预测的后果,(3)选择最佳行动。限制我们研究审议决策能力的一个重要困难是审议过程是隐蔽的,即所考虑的瞬时信息不会反映在立即的行为中。然而,新的数学技术现在允许以非常快的时间尺度从神经集合中解码所表示的变量,从而能够观察这些瞬时的、隐蔽的过程。这个提议的目标是跟踪在评估替代方案时对奖励结果的隐蔽预测。我们有初步的数据表明,已知参与动机和评价的结构(腹侧纹状体,眶额皮质)在某些深思熟虑的决策点上显示出短暂的奖励相关活动激活。结合新的多结构记录技术,新开发的任务,新改进的神经集成分析技术和计算建模,我们将研究海马体中未来可能性的表征与奖励相关信息在已知参与动机,奖励和决策的结构中的隐蔽再现之间的关系。

项目成果

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A DAVID REDISH其他文献

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{{ truncateString('A DAVID REDISH', 18)}}的其他基金

Computational Core
计算核心
  • 批准号:
    10377370
  • 财政年份:
    2020
  • 资助金额:
    $ 7.3万
  • 项目类别:
Dysfunctional State Representations in Psychosis: From Neurophysiology to Neuroplasticity-based Treatment
精神病中的功能障碍状态表征:从神经生理学到基于神经可塑性的治疗
  • 批准号:
    10377362
  • 财政年份:
    2020
  • 资助金额:
    $ 7.3万
  • 项目类别:
Computational Core
计算核心
  • 批准号:
    10597084
  • 财政年份:
    2020
  • 资助金额:
    $ 7.3万
  • 项目类别:
Dysfunctional State Representations in Psychosis: From Neurophysiology to Neuroplasticity-based Treatment
精神病中的功能障碍状态表征:从神经生理学到基于神经可塑性的治疗
  • 批准号:
    10597064
  • 财政年份:
    2020
  • 资助金额:
    $ 7.3万
  • 项目类别:
Predoctoral Training of Neuroscientists
神经科学家的博士前培训
  • 批准号:
    10414079
  • 财政年份:
    2018
  • 资助金额:
    $ 7.3万
  • 项目类别:
Predoctoral Training of Neuroscientists
神经科学家的博士前培训
  • 批准号:
    10189718
  • 财政年份:
    2018
  • 资助金额:
    $ 7.3万
  • 项目类别:
Using Computation to Achieve Breakthroughs in Neuroscience
利用计算实现神经科学的突破
  • 批准号:
    10437791
  • 财政年份:
    2018
  • 资助金额:
    $ 7.3万
  • 项目类别:
Predoctoral Training of Neuroscientists
神经科学家的博士前培训
  • 批准号:
    10626176
  • 财政年份:
    2018
  • 资助金额:
    $ 7.3万
  • 项目类别:
Testing hybrid theories of action-selection
测试行动选择的混合理论
  • 批准号:
    10605295
  • 财政年份:
    2017
  • 资助金额:
    $ 7.3万
  • 项目类别:
Resolving conflicts between decision-making algorithms
解决决策算法之间的冲突
  • 批准号:
    9284763
  • 财政年份:
    2017
  • 资助金额:
    $ 7.3万
  • 项目类别:

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