Representations Yielding Task-Dependent Behavior

描述（由申请人提供）：本研究的主要目标是促进对任务依赖行为的表征的理解。婴儿和儿童可能会出现早熟或几乎任何能力都受到限制，这取决于给予他们的任务。例如，在违反预期研究中，3.5个月大的婴儿似乎理解隐藏物体的持续存在，但婴儿直到9个月左右才能手动搜索被遮挡物隐藏的物体。同样，孩子们可以回答关于如何在不同情况下灵活应对的口头询问，但他们在实际行为中无法表现出这种灵活性。这种任务依赖性行为，或解离，提出了关于我们认知系统的组织，发展和训练的重要问题。本项目通过以下问题调查这些问题： 1.）的人。什么样的表征会导致任务依赖行为，具体来说：分级表征如何促进任务依赖行为？不同类型的表征（主动表征和潜在表征）是如何影响任务依赖行为的？不同等级和不同类型的表征如何相互作用以影响行为？ 2.）的情况。为理解婴儿和儿童的任务依赖性行为而提出的分级的主动-潜伏框架的普遍性如何，具体而言：需要对该框架的计算模型进行哪些修订，以更充分地解释行为和生物学发现？这一框架的潜在教育意义是什么？这个框架与理解成人行为有什么相关性？拟议的研究通过整合行为测试、神经网络建模和认知神经科学的发现来调查这些问题。 拟议的工作提供了一个连贯的程序，以促进我们对任务依赖行为的因素的理解-这是表征知识表征性质的重要一步，反过来又为理论及其在典型和特殊人群中的应用提供了信息。

DESCRIPTION (provided by applicant): The primary goal of this research is to advance understanding of the representations underlying task-dependent behavior. Infants and children can appear precocious or limited in almost any ability depending on the task administered to them. For example, infants as young as 3.5 months seem to understand the continued existence of hidden objects in violation-of-expectation studies, yet infants fail to manually search for objects hidden by occluders until around 9 months. Similarly, children can answer verbal queries about how to respond flexibly in different situations, yet they fail to show such flexibility in their actual behaviors. Such task-dependent behaviors, or dissociations, raise important questions about the organization, development, and training of our cognitive systems. This project investigates these issues via the following questions: 1.) What kinds of representations lead to task-dependent behaviors, specifically: How do graded representations contribute to task-dependent behaviors? How do distinct types of representations (active and latent) contribute to task-dependent behaviors? How do graded and distinct types of representations interact to influence behavior? 2.) How general is the graded, active-latent framework proposed for understanding infants' and children's task-dependent behaviors, specifically: What revisions are required for computational models of this framework to more fully account for behavioral and biological findings? What are the potential educational implications from this framework? What is the relevance of this framework for understanding adult behavior? The proposed studies investigate these questions through the integration of behavioral testing, neural network modeling, and findings from cognitive neuroscience. The proposed work provides a coherent program for advancing our understanding of the factors contributing to task-dependent behavior -- an essential step toward characterizing the nature of representations of knowledge, and in turn informing theory and its application to both typical and special populations.