Developmental trajectories of emotional learning and episodic memory

情绪学习和情景记忆的发展轨迹

• 批准号: 1714321
• 负责人: Alexandra Cohen
• 金额: $ 13.8万
• 依托单位: Cohen Alexandra
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1714321&HistoricalAwards=false
• 关键词: Developmental; trajectories; emotional; learning; episodic

This award was provided as part of NSF's 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. The ability to learn from and remember salient information in the environment is essential for an individual to survive and thrive throughout the lifespan. During the transition to adulthood, adolescents navigate a dynamic environment filled with new and often emotional experiences. Actions in emotional situations, during this time of heightened emotional sensitivity, can result in poor decision-making and negative outcomes, including increased incidence of psychopathology and preventable death. Normative developmental changes in emotional learning and the emotional facilitation of episodic memory may contribute to adolescents' unique behavior in emotionally charged contexts. A rich literature examining classical conditioning has highlighted how the emotional significance of stimuli fluctuates as the statistics of the environment change. Recent work suggests that qualitative differences in the cognitive representations formed during dynamic emotional learning may modulate the persistence of emotional memories. Still, little is known about how this variation emerges, in both behavior and brain, across development or how these changes may influence episodic memory. The proposed research uses a computational model of classical conditioning to examine individual differences in emotional learning and episodic memory across development. By leveraging computational, neuroimaging, and behavioral approaches to better understand developmental changes in how individuals learn and remember the structure of the emotional environment, this research may shed light on the neurocognitive processes that promote healthy development of motivated behaviors. The insights from the proposed research will have implications for affective, developmental, and computational cognitive neuroscience each independently, and for bridging the three research fields. The proposed research uses a formalized computational model of classical conditioning to examine individual differences in emotional learning and episodic memory across development. This project will expand on and integrate several lines of research by investigating: 1) developmental trajectories of individual differences in emotional learning, 2) the utility of a computational model of conditioning for making predictions about engagement of neural circuitry underlying emotional learning, and 3) how individual differences in emotional learning may influence episodic memory for category-specific items presented during learning. We will implement computational modeling of psychophysiological emotional learning data, analyze neural activity and functional connectivity during emotional learning, and examine how emotional learning influences episodic memory across development. We hypothesize that the increase in emotionally driven behaviors observed during adolescence may be reflective of normative developmental changes in the cognitive structure of emotional learning and memory processes. This research program will provide an important contribution to the sparse literature examining emotional learning and underlying neural circuitry in humans from childhood to adulthood, modeling age continuously in order to determine distinct patterns of age-related change. These data will also be the first to characterize the neural correlates of a computational model of threat learning across development in humans and to extend the model predictions to the effects of emotional learning on episodic memory, also across development. This project builds on prior work examining negative emotion, but we predict results will be similar examining positive emotion. This work will serve as a foundation for future studies using computational modeling approaches to study individual differences in the cognitive structure of learning and memory across development. These data may ultimately help identify ways to take advantage of individual differences and developmental changes in emotional learning and memory to help optimize learning and bolster healthy development.

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 项目的目标是为学术界、工业界或私营部门以及政府的科学职业培养有前途的早期职业博士级科学家。 SPRF 奖项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 致力于促进科学界各个领域的科学家（包括来自代表性不足群体的科学家）参与其研究计划和活动；博士后时期被认为是实现这一目标的重要专业发展阶段。每个博士后研究员必须解决推动各自学科领域发展的重要科学问题。从环境中学习和记住显着信息的能力对于个体在一生中生存和发展至关重要。在向成年过渡的过程中，青少年处于一个充满新的且往往是情感体验的动态环境中。在情绪敏感度较高的时期，在情绪情况下采取的行动可能会导致决策失误和负面结果，包括精神病理学和可预防死亡的发生率增加。情绪学习的规范性发展变化和情景记忆的情绪促进可能有助于青少年在情绪激动的环境中的独特行为。大量研究经典条件作用的文献强调了刺激的情感意义如何随着环境统计数据的变化而波动。最近的研究表明，动态情绪学习过程中形成的认知表征的质性差异可能会调节情绪记忆的持久性。尽管如此，人们对这种变化如何在行为和大脑中、在整个发育过程中出现或这些变化如何影响情景记忆知之甚少。拟议的研究使用经典条件反射的计算模型来检查情绪学习和情景记忆在发展过程中的个体差异。通过利用计算、神经影像和行为方法来更好地了解个体学习和记忆情绪环境结构的发展变化，这项研究可能会揭示促进动机行为健康发展的神经认知过程。拟议研究的见解将对情感、发育和计算认知神经科学各自独立产生影响，并连接这三个研究领域。拟议的研究使用经典条件反射的形式化计算模型来检查情绪学习和情景记忆在发展过程中的个体差异。该项目将通过调查扩展和整合多个研究方向：1）情绪学习中个体差异的发展轨迹，2）条件计算模型在预测情绪学习背后的神经回路参与方面的效用，以及3）情绪学习中的个体差异如何影响学习过程中呈现的特定类别项目的情景记忆。我们将对心理生理学情绪学习数据进行计算建模，分析情绪学习过程中的神经活动和功能连接，并研究情绪学习如何影响整个发展过程中的情景记忆。我们假设，青春期期间观察到的情绪驱动行为的增加可能反映了情绪学习和记忆过程的认知结构的规范发展变化。该研究项目将为研究人类从童年到成年的情绪学习和潜在神经回路的稀疏文献做出重要贡献，持续建模年龄以确定与年龄相关的变化的不同模式。这些数据也将首次表征人类发展过程中威胁学习计算模型的神经关联，并将模型预测扩展到情绪学习对情景记忆（也包括发展过程）的影响。该项目建立在之前检查消极情绪的工作的基础上，但我们预测结果将与检查积极情绪类似。这项工作将为未来的研究奠定基础，使用计算建模方法来研究学习和记忆在发展过程中的认知结构的个体差异。这些数据最终可能有助于找到利用情绪学习和记忆的个体差异和发展变化的方法，以帮助优化学习和促进健康发展。

项目成果

Aversive learning strengthens episodic memory in both adolescents and adults

• DOI: 10.1101/lm.048413.118
• 发表时间: 2019-07-01
• 期刊: LEARNING & MEMORY
• 影响因子: 2
• 作者: Cohen，Alexandra O.;Matese，Nicholas G.;Hartley，Catherine A.
• 通讯作者: Hartley，Catherine A.