Charting the role of variability in learning across development

绘制学习过程中可变性的作用

• 批准号: 10455806
• 负责人: Rebecca E Martin
• 金额: $ 0.25万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10455806
• 关键词: Address; Adolescent; Adult; Age; Attention deficit hyperactivity disorder; Basic Science; Behavioral; Categories; Child; Childhood; Clinical; Complex; Computer Models; Development; Diagnostic; Early Diagnosis; Entropy; Environment; Exhibits; Functional Magnetic Resonance Imaging; Future; Goals; High temperature of physical object; Individual; Integration Host Factors; Knowledge; Lateral; Lead; Learning; Learning Disabilities; Literature; Measures; Medial; Methods; Modeling; Neurodevelopmental Disorder; Outcome; Participant; Pattern; Prefrontal Cortex; Process; Psychological reinforcement; Reaction Time; Research; Research Personnel; Research Proposals; Risk; Role; Sampling; Short-Term Memory; Stimulus; Temperature; Testing; Time; Work; autism spectrum disorder; cognitive development; cognitive neuroscience; cognitive skill; cognitive task; cold temperature; computer science; design; executive function; experience; imaging modality; indexing; neuroimaging; neuromechanism; recruit; relating to nervous system; research and development; response; selective attention; skills; theories

Project Summary/Abstract The way individuals learn from their environment reliably changes with age and experience. A common pattern observed across a wide range of cognitive tasks is that younger children tend to exhibit greater variability in accuracy, reaction time, and other general response patterns, and this variability decreases both within and between subjects with increasing age. While this increased variability is widely acknowledged as a feature of development, the neural and computational processes underlying such variability remain to be discovered, and its potential functions for learning remain poorly characterized. The goal of this research proposal is to chart behavioral and neural variability associated with changes and improvements in learning across development. To accomplish this goal, we will apply computational modeling and neuroimaging methods to better discriminate patterns of variability observed in children during learning, and the variability reduction process that takes place with maturation. We will explore two key measures of variability: (1) the process of exploration of choices during learning, and (2) the development of strategies used to test hypotheses about the regularities of the information to be learned. Comparing a continuous sample of children through adults, we will test three core predictions. First, in Aim 1 we predict that children will show greater variability in the form of greater exploration and choice stochasticity in an explore-exploit reinforcement learning task, and this pattern of exploration will decrease with age. Second, in Aim 2 we hypothesize that when forming strategies in order to learn how to best classify stimuli in a simple perceptual categorization task, children will demonstrate greater variability by using a random guessing strategy for a longer duration and switching between strategies more often than adults. Third, we hypothesize that these behavioral effects will be modulated by late maturing prefrontal cortical regions - the frontopolar cortex during exploration, and medial prefrontal cortex during strategy formation – and the degree of activation in these regions will increase in magnitude with age. No previous study has simultaneously examined both the behavioral and neural processes underlying exploration and strategy use during learning across development. As such, we hope to gain a more detailed and nuanced understanding of how precise measures of variability can elucidate developmental differences in the way we learn. By better clarifying the process of variability reduction in learning during development, this research may inform future translational work in identifying when and how the cognitive development of a child or adolescent may not be following a normative trajectory. This knowledge can aid in designing better early diagnostic measures for individuals at risk of developing learning disabilities or neurodevelopmental disorders associated with greater neural and behavioral variability such as ADHD and autism.

项目概要/摘要 个人从环境中学习的方式会随着年龄和经验的变化而发生变化。 在广泛的认知任务中观察到的模式是，年幼的孩子往往表现出更大的能力 准确性、反应时间和其他一般响应模式的可变性，并且这种可变性降低了 随着年龄的增长，受试者内部和受试者之间的差异被广泛认为是一种差异。 发展的特征，这种可变性背后的神经和计算过程仍然有待进一步研究。 已被发现，但其潜在的学习功能仍不清楚。 提议是绘制与学习变化和改进相关的行为和神经变异性图表 为了实现这一目标，我们将应用计算模型和神经影像学。 更好地区分儿童在学习过程中观察到的变异模式的方法以及变异 随着成熟而发生的减少过程我们将探讨两个关键的变异性指标：（1） 学习过程中探索选择的过程，以及（2）制定用于测试的策略 关于要学习的信息的规律性的假设 比较连续的儿童样本。 通过成人，我们将测试三个核心预测，首先，在目标 1 中，我们预测儿童会表现得更好。 探索-利用强化中更大的探索和选择随机性形式的可变性 其次，我们在目标 2 中捕捉到了这一点。 当形成策略以学习如何在简单的感知分类任务中最好地对刺激进行分类时， 通过长时间使用随机猜测策略，孩子们将表现出更大的可变性，并且 第三，我们认为这些行为效应会比成年人更频繁地切换。 受到晚熟前额皮质区域的调节 - 探索期间的额极皮质和内侧 战略形成过程中的前额皮质——这些区域的激活程度将在 以前没有研究同时检查行为和神经的变化。 因此，我们希望能够在跨发展的学习过程中处理潜在的探索和策略的使用。 更详细和细致地了解变异性的精确测量如何能够阐明 我们学习方式的发展差异通过更好地阐明减少可变性的过程。 在开发过程中学习，这项研究可能会为未来的转化工作提供信息，以确定何时以及如何 儿童或青少年的认知发展可能不遵循规范的轨迹。 可以帮助为有学习障碍风险的个人设计更好的早期诊断措施，或 与更大的神经和行为变异相关的神经发育障碍，例如多动症和 自闭症。