Dynamics of Representational Change

表征是认知科学和几乎所有心理学分支的核心理论结构。它捕捉到了许多生物体的非凡能力，即明显地提取和内化有关外部环境的信息。人类和许多其他物种都能根据自己的过去清楚地预测未来。表征的发展允许我们这样做，从而打开了认知之门。拟议的研究调查了广泛的假设，即表征是从认知系统（一个系统，包括大脑和身体）的动态涌现。因此，表征就像其他结构一样，是为了保持系统的组织性而出现的--没有组织，有机体就停止了功能。这个看似没有争议的想法，即表象的出现是为了增加系统内的秩序，这表明非线性动力学的自组织原理可能适用。在非线性动力学中，新的结构以熵的形式出现（即，在开放系统中，增长。新结构的功能是耗散熵，从而通过减少内部熵来保持系统的完整性。该项目涉及表征变化中三个主要现象的动力学：归纳，假设检验和迁移。这些研究结合了联合收割机运动跟踪技术和分析长期数据的方法，以预测3.5 - 12岁儿童新表征的开始。该项目建立在以前的工作与儿童和成人在齿轮系统的范例;参与者被要求预测的转动方向的最后一个齿轮的系列，给定的转动方向的驱动齿轮。先前的研究表明，参与者：a）在这个任务中诱导一个新的表征基于他们自己的行动; B）通过假设检验改变他们的表征;和c）转移关系从一个结构相似的域。目前的工作将调查的变化，在潜在的动态组织的系统，引起这些关键方面的表征变化。该项目将促进我们对知识获取的理解，因此对儿童的学习具有影响。这项研究对认知科学的理论也有深刻的影响，因为它弥合了动力学和认知之间的鸿沟。

Representation is a core theoretical construct for cognitive science and nearly all branches of psychology. It captures the remarkable ability of many organisms to apparently extract and internalize information about the external environment. Humans and many other species clearly predict the future, based on their past. The development of representations allows us to do so, thereby opening the door to cognition. The proposed research investigates the broad hypothesis that representations are emergent from the dynamics of the cognitive system (a system that includes brain and body). On this account, representations, like other structures, emerge to keep the system organized - without organization the organism ceases to function. This seemingly non-controversial idea, that representations emerge to increase order within the system, suggests that principles of self-organization from nonlinear dynamics may apply. In nonlinear dynamics, new structures emerge as the entropy (i.e., disorder) within an open system increases. The new structures function to dissipate that entropy, thus maintaining the system's integrity by decreasing its internal entropy. The project addresses the dynamics underlying three major phenomena in representational change: induction, hypothesis testing, and transfer. The studies combine motion-tracking technology and methods for analyzing over-time data to predict the onset of new representations in children aged 3.5 - 12 years. The project builds on previous work with children and adults in a gear-system paradigm; participants are asked to predict the turning direction of the final gear in the series, given the turning direction of the driving gear. Previous research showed that participants: a) induce a new representation during this task based on their own actions; b) change their representations via hypothesis testing; and c) transfer relations from a structurally analogous domain. The current work will investigate the changes in underlying dynamical organization of the system that give rise to these key aspects of representational change. The project will advance our understanding of knowledge acquisition and, therefore, has implications for children's learning. The research also has deep implications for theories within cognition science, because it bridges the current gap between dynamics and cognition.