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

博士后奖学金：SPRF：采用计算方法来理解模式内存交互

• 批准号: 2313703
• 负责人: Michelle Ramey
• 金额: $ 16万
• 依托单位: Ramey, Michelle M
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313703&HistoricalAwards=false
• 关键词: Postdoctoral; Fellowship; SPRF; Taking; Computational

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.

该奖项是NSF社会，行为和经济科学博士后研究奖学金（SPRF）计划的一部分。SPRF计划的目标是为学术界，工业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的奖励包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。NSF致力于促进来自科学界各部门的科学家，包括来自代表性不足的群体的科学家参与其研究计划和活动;博士后期间被认为是实现这一目标的专业发展的重要水平。每个博士后研究员必须解决推进各自学科领域的重要科学问题。在阿肯色州大学的詹姆斯·兰皮宁博士和格兰特·希尔兹博士的赞助下，这个博士后奖学金支持了一位研究图式-记忆相互作用的早期职业科学家。记忆力丧失是衰老最可怕和最有害的后果之一，但是当老年人的先验知识（即，模式）与他们试图记住的内容一致（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。当他们的先验知识与要记住的信息相冲突时（例如，记住药物是在一个不寻常的地方，如冰箱），然而，老年人有更多的困难记住这些信息。尽管了解记忆随年龄增长而丧失的重要性，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。该项目将通过结合使用尖端方法-计算认知模型开发和新的眼动跟踪指标-来解决这一差距，以测试新的机制，并提出一种新的理论，解释为什么老年人的记忆会受到图式一致性的影响。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记忆和衰老的理解。此外，这些发现有望为未来开发针对衰老记忆衰退的干预措施提供基础，例如针对在记忆决策中使用图式的干预措施。拟议研究的目标是：1）开发两个新的计算认知模型，以评估图式-记忆相互作用的动力学基础，（2）利用这些模型和眼动追踪技术探讨图式对记忆影响的年龄差异机制，并检验一个新的理论。年长和年轻的成年参与者将在场景中搜索图式一致和图式不一致的对象，完成空间回忆和场景识别记忆测试，并完成与图式相关的场景评级任务。眼动追踪数据将在整个过程中收集。将开发一个计算认知模型来捕捉图式-记忆交互如何随着时间的推移而展开，并开发另一个模型来捕捉它们在记忆决策中的权重。拟议的研究将通过开发和传播可用于回答记忆研究中未来问题的新模型，首次直接测试先前理论化的机制，识别先前未被考虑的新机制，该奖项反映了NSF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。