CAREER: Modeling Response-Time Distributions to Test Theories of Event Memory

职业:建模响应时间分布以测试事件记忆理论

基本信息

  • 批准号:
    1454868
  • 负责人:
  • 金额:
    $ 51.6万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-07-01 至 2022-06-30
  • 项目状态:
    已结题

项目摘要

Memory for previously experienced events can take many forms, such as deciding whether a person's face was seen previously versus deciding where a person's face was seen previously. Different theories make different assumptions about how these various forms of memory come about. Whereas some theories assume that the ability to call to mind a prior experience is all-or-none (it either occurs or does not), other theories assume that bits of information accumulate in a continuous manner from less to more. Yet other theories assume that both an all-or-none ability to call something to mind and a process of continuously accumulating information co-exist, and either mechanism can underlie memory in a given situation (it is a matter of teasing them apart). Determining the true state of affairs is important for a number of reasons, including the development of appropriate methods for assessing eyewitness memory, the development of appropriate tools for assessing cognitive functions in cases of memory impairment, and the development of appropriate memory tasks for use in research on the neural underpinnings of memory. This CAREER project by an early career stage investigator aims to differentiate among existing models of human event memory by imposing constraints not typically used by researchers. Previous modeling efforts have led to somewhat of an impasse regarding understanding human event memory because vastly different models are all able to accommodate human data patterns produced in empirical studies of how memory accuracy varies across experimental conditions. In addition to the typically-used accuracy measures of memory, this project will use response time measures to further constrain the data needing to be accommodated by the models in order to better force differentiation among the possible theoretical alternatives. Across a number of experiments, various experimental manipulations will be used in conjunction with these measures to provide even further constraints to help to rule models out and potentially identify a candidate model for how human event memory most likely operates. As part of the education component of the CAREER plan, the investigator will create a computational modeling concentration within the Psychology major, providing undergraduate students with a unique opportunity to develop cognitive modeling skills. He will also make the modeling tools from the research available to the research community via a website.
对先前经历的事件的记忆可以采取多种形式,例如决定一个人的脸以前是否被看到,而不是决定一个人的脸以前在哪里被看到。不同的理论对这些不同形式的记忆是如何产生的做出了不同的假设。有些理论认为,唤起先前经历的能力是全有或全无的(要么发生,要么不发生),而另一些理论则认为,信息比特是以从少到多的连续方式积累的。然而,其他理论认为,一种要么全有要么全无的唤起记忆的能力和一个不断积累信息的过程共存,并且任何一种机制都可以成为特定情况下记忆的基础(这是一个将它们区分开来的问题)。确定事件的真实状态很重要,原因有很多,包括开发评估目击者记忆的适当方法,开发评估记忆障碍情况下认知功能的适当工具,以及开发用于记忆神经基础研究的适当记忆任务。这个由职业生涯早期阶段的研究人员进行的CAREER项目旨在通过施加研究人员通常不使用的限制来区分现有的人类事件记忆模型。以前的建模工作导致了一些关于理解人类事件记忆的僵局,因为非常不同的模型都能够适应人类的数据模式,这些数据模式是在记忆准确性如何在实验条件下变化的实证研究中产生的。除了通常使用的记忆精度测量外,该项目还将使用响应时间测量来进一步限制模型需要容纳的数据,以便更好地区分可能的理论替代方案。在许多实验中,各种实验操作将与这些措施结合使用,以提供更进一步的约束,以帮助排除模型,并可能识别人类事件记忆最可能如何运作的候选模型。作为职业生涯计划的教育组成部分的一部分,调查员将在心理学专业内创建计算建模集中,为本科生提供发展认知建模技能的独特机会。他还将通过网站向研究界提供研究中的建模工具。

项目成果

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Jeffrey Starns其他文献

Jeffrey Starns的其他文献

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{{ truncateString('Jeffrey Starns', 18)}}的其他基金

Effect of Visualization on Undergraduate Students' Understanding of Fundamental Probability Concepts, Including Bayesian Inference
可视化对本科生理解基本概率概念(包括贝叶斯推理)的影响
  • 批准号:
    1842537
  • 财政年份:
    2019
  • 资助金额:
    $ 51.6万
  • 项目类别:
    Standard Grant

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