Developmental trajectories of emotional learning and episodic memory

该奖项是作为NSF社会、行为和经济学博士后研究奖学金(SPRF)计划的一部分提供的。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职业生涯培养有前途的、早期职业博士水平的科学家。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。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。从环境中学习和记忆重要信息的能力对于一个人在一生中生存和茁壮成长至关重要。在过渡到成年的过程中，青少年在充满新的、往往是情绪化的体验的动态环境中导航。在情绪高度敏感的这段时间里，在情绪情况下的行为可能会导致糟糕的决策和负面结果，包括增加精神病和可预防的死亡的发生率。情绪学习的规范性发展变化和情景记忆的情绪化可能有助于青少年在情绪化背景下的独特行为。一篇研究经典条件反射的丰富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。最近的工作表明，在动态情绪学习过程中形成的认知表征的质的差异可能调节情绪记忆的持久性。尽管如此，对于这种变化是如何在行为和大脑发育过程中出现的，或者这些变化如何影响情景记忆，我们知之甚少。这项拟议的研究使用经典条件反射的计算模型来考察个体在情绪学习和情景记忆发展过程中的差异。通过利用计算、神经成像和行为方法更好地了解个体学习和记忆情绪环境结构的发展变化，这项研究可能有助于揭示促进动机行为健康发展的神经认知过程。这项拟议研究的洞察力将分别对情感、发展和计算认知神经科学产生影响，并将这三个研究领域联系起来。这项拟议的研究使用了经典条件反射的正式计算模型来考察个体在情绪学习和情景记忆发展过程中的差异。这个项目将通过调查以下几个方面来扩展和整合几个研究方向：1)情绪学习中个体差异的发展轨迹；2)条件反射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；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通性，并研究情绪学习如何影响情景记忆的发展。我们假设，在青春期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正常发展变化。这项研究计划将为研究人类从童年到成年的情感学习和潜在神经回路的稀少文献做出重要贡献，连续对年龄进行建模，以确定与年龄相关的明显变化模式。这些数据还将首次描述人类发育过程中威胁学习的计算模型的神经相关性，并将模型预测扩展到情绪学习对情景记忆的影响，也是跨发育的。这个项目建立在之前研究负面情绪的基础上，但我们预测检测积极情绪的结果将是相似的。这项工作将作为未来研究的基础，使用计算建模方法来研究学习和记忆认知结构在发展过程中的个体差异。这些数据最终可能有助于确定利用个体差异和情绪学习和记忆方面的发展变化来帮助优化学习和支持健康发展的方法。

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.