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Changes of mind in decision-making

机译:决策改变

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摘要

A decision is a commitment to a proposition or plan of action based on evidence and the expected costs and benefits associated with the outcome. Progress in a variety of fields has led to a quantitative understanding of the mechanisms that evaluate evidence and reach a decision. Several formalisms propose that a representation of noisy evidence is evaluated against a criterion to produce a decision. Without additional evidence, however, these formalisms fail to explain why a decision-maker would change their mind. Here we extend a model, developed to account for both the timing and the accuracy of the initial decision, to explain subsequent changes of mind. Subjects made decisions about a noisy visual stimulus, which they indicated by moving a handle. Although they received no additional information after initiating their movement, their hand trajectories betrayed a change of mind in some trials. We propose that noisy evidence is accumulated over time until it reaches a criterion level, or bound, which determines the initial decision, and that the brain exploits information that is in the processing pipeline when the initial decision is made to subsequently either reverse or reaffirm the initial decision. The model explains both the frequency of changes of mind as well as their dependence on both task difficulty and whether the initial decision was accurate or erroneous. The theoretical and experimental findings advance the understanding of decision-making to the highly flexible and cognitive acts of vacillation and self-correction.
机译:决定是对证据或与结果相关的预期成本和收益的承诺或行动计划的承诺。各个领域的进展已导致人们对评估证据并做出决定的机制有了定量的了解。几种形式主义建议根据标准对嘈杂证据的表示进行评估以做出决定。但是,如果没有其他证据,这些形式主义就无法解释为什么决策者会改变主意。在这里,我们扩展了一个模型,该模型旨在说明初始决策的时机和准确性,以解释其后的想法变化。受试者做出了有关嘈杂的视觉刺激的决定,他们通过移动手柄来表明这一点。尽管他们在开始运动后没有收到任何其他信息,但在某些试验中,他们的手部轨迹出乎了主意。我们建议,随着时间的推移,嘈杂的证据会不断积累,直到达到确定初始决策的标准水平或界限为止,并且当做出初始决策以随后反转或重申该决策时,大脑会利用处理流程中的信息。初步决定。该模型既说明了改变思想的频率,也说明了他们对任务难度的依赖性以及初始决定是准确还是错误的。理论上和实验上的发现将决策的理解推进到高度灵活的认知行为以及动摇和自我纠正。

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  • 来源
    《Nature》 |2009年第7261期|263-266|共4页
  • 作者单位

    Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK Howard Hughes Medical Institute, Janelia Farm Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA;

    Howard Hughes Medical Institute. National Primate Research Center and Department of Physiology and Biophysics, University of Washington, Seattle, Washington 98195, USA;

    Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK;

    Howard Hughes Medical Institute. National Primate Research Center and Department of Physiology and Biophysics, University of Washington, Seattle, Washington 98195, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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