Postdoctoral Fellowship: SPRF: Taking a Computational Approach to Understanding Schema-Memory Interactions

该奖项是美国国家科学基金会社会、行为和经济科学博士后研究奖学金（SPRF）项目的一部分。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。在博士的赞助下。阿肯色大学的詹姆斯·兰皮宁和格兰特·希尔兹，这个博士后奖学金支持一位早期职业科学家研究图式-记忆相互作用。记忆丧失是衰老最可怕和最有害的后果之一，但当老年人的先验知识（即图式）与他们试图记住的内容一致时（例如，记住药物在药柜里），老年人的记忆与年轻人的记忆相似。然而，当他们先前的知识与要记住的信息相冲突时（例如，记住药物放在像冰箱这样的不寻常的地方），老年人更难记住这些信息。尽管理解记忆随着年龄的增长而丧失是很重要的，但目前尚不清楚老年人的记忆如何或为什么在图式一致和图式不一致的信息之间存在如此显著的差异。该项目将通过使用尖端方法——计算认知模型开发和新的眼球追踪指标——来解决这一差距，以测试新的机制，并提出一个新的理论，解释为什么老年人的记忆如此受图式一致性的影响。这些发现以及我们开发的新的计算模型有望大大推进该领域对一般记忆和衰老的理解。此外，这些研究结果有望为未来发展针对记忆决策中图式使用的干预措施提供基础。本研究的目的是：(1)建立两种新的计算认知模型，以评估图式-记忆相互作用的动态机制；(2)利用这些模型和眼动追踪来探索图式对记忆影响的年龄差异机制，并验证一种新的理论。年龄较大和较年轻的被试将在场景中寻找与场景一致和不一致的对象，完成空间回忆和场景识别记忆测试，并完成与场景相关的场景评分任务。眼球追踪数据将全程收集。一个计算认知模型将被开发来捕捉图式-记忆相互作用如何随着时间的推移而展开，另一个模型将被开发来捕捉它们如何在记忆决策中加权。本研究旨在通过发展和传播新的模型来回答记忆研究中的未来问题，首次直接测试先前的理论机制，确定以前未被考虑的新机制，并提出一个新的理论来调和相互竞争的理论，从而大大提高我们对图式-记忆相互作用和衰老的理解。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award was provided as part of the NSF Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Drs. James Lampinen and Grant Shields at the University of Arkansas, this postdoctoral fellowship award supports an early career scientist investigating schema-memory interactions. Loss of memory is one of the most feared and detrimental consequences of aging--but when older adults' prior knowledge (i.e., schema) is consistent with what they are trying to remember (e.g., remembering medication is in a medicine cabinet), older adults' memory is similar to younger adults' memory. When their prior knowledge is conflicting with to-be-remembered information (e.g., remembering medication is in an unusual place like the fridge), however, older adults have more difficulty remembering that information. Despite the importance of understanding memory loss with age, it is not known how or why older adults' memory differs so markedly between schema-consistent and schema-inconsistent information. This project will address this gap by using a combination of cutting-edge methods--computational cognitive model development and new eyetracking metrics--to test new mechanisms and put forth a new theory of why older adults' memory is so affected by schema consistency. The findings as well as the novel computational models we develop are expected to substantially advance the field's understanding of memory in general and in aging. Moreover, these findings are expected to provide a foundation for the future development of interventions for memory decline in aging, such as interventions targeting the use of schemas in memory decisions.The aims of the proposed research are 1) to develop two new computational cognitive models that allow the dynamics underlying schema-memory interactions to be assessed, and 2) to use these models as well as eyetracking to probe mechanisms underlying age differences in schema effects on memory and test a new theory. Older and younger adult participants will search for schema-congruent and schema-incongruent objects in scenes, complete a spatial recall and scene recognition memory test, and complete a schema-related scene rating task. Eyetracking data will be collected throughout. One computational cognitive model will be developed to capture how schema-memory interactions unfold over time, and another model will be developed to capture how they are weighted in memory decisions. The proposed research stands to substantially advance our understanding of schema-memory interactions in general and in aging by developing and disseminating new models that can be used to answer future questions in memory research, directly testing previously theorized mechanisms for the first time, identifying new mechanisms that had not previously been considered, and putting forward a new theory that stands to reconcile competing theories.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.