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Examining recognition criterion rigidity during testing using a biased feedback technique: Evidence for adaptive criterion learning

机译:使用偏向反馈技术在测试过程中检验识别标准的刚性:自适应标准学习的证据

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摘要

Recognition models often assume that subjects use specific evidence values (decision criteria) to adaptively parse continuous memory evidence into response categories (e.g., “old” or “new”). Although explicit pre-test instructions influence criterion placement, these criteria appear extremely resistant to change once testing begins. We tested criterion sensitivity to local feedback using a novel, biased feedback technique designed to tacitly encourage certain errors by indicating they were correct choices. Experiment 1 demonstrated that fully correct feedback had little effect on criterion placement, whereas biased feedback during Experiments 2 and 3 yielded prominent, durable, and adaptive criterion shifts, with observers reporting they were unaware of the manipulation in Experiment 3. These data suggest recognition criteria can be easily modified during testing through a form of feedback learning that operates independent of stimulus characteristics and observer awareness of the nature of the manipulation. This mechanism may be fundamentally different than criterion shifts following explicit instructions and warnings, or shifts linked to manipulations of stimulus characteristics combined with feedback highlighting those manipulations.
机译:识别模型通常假设受试者使用特定的证据值(决策标准)将连续记忆证据自适应地解析为响应类别(例如“旧”或“新”)。尽管明确的测试前指令会影响准则的位置,但是一旦开始测试,这些准则就显得极难改变。我们使用一种新颖的,偏向的反馈技术测试了标准对本地反馈的敏感性,该技术旨在通过指示某些错误是正确的选择来默认鼓励某些错误。实验1表明,完全正确的反馈对准则放置几乎没有影响,而实验2和3期间的偏差反馈则产生了明显,持久和自适应的准则偏移,观察者报告说他们不知道实验3中的操纵。这些数据表明了识别准则在测试过程中,可以通过一种反馈学习形式轻松修改该反馈学习形式,该形式独立于刺激特性和观察者对操纵性质的了解而进行操作。该机制可能与显式指令和警告之后的标准转换或与刺激特征操作相结合的转换(与突出显示这些操作的反馈)根本不同。

著录项

  • 期刊名称 other
  • 作者

    Sanghoon Han; Ian G. Dobbins;

  • 作者单位
  • 年(卷),期 -1(36),4
  • 年度 -1
  • 页码 703–715
  • 总页数 22
  • 原文格式 PDF
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