Dynamic and adaptive body schema by learning to predict the sensory consequences of actions

通过学习预测动作的感官后果来实现动态和自适应的身体模式

• 批准号: 402781479
• 负责人: Professor Dr.-Ing. Fred Henrik Hamker
• 金额: --
• 依托单位: Berlin School of Mind and Brain
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/402781479?language=en
• 关键词: Dynamic; adaptive; body; schema; learning

Our project proposal addresses the co-development of a body schema and of agency (predicting the sensory consequences of one's own actions) in an interdisciplinary way.The interdisciplinary components are: i) Theoretical/conceptual: Based on data from human studies and basic neuro-scientific findings, we developed a concrete design concept of integral mechanisms required for explaining body ownership and agency on a neural systems level of brain function. This conceptual model has guided experimental setups to further evaluate this model together with our partners. ii) Computational neuroscience methods: The conceptual model (representing parietal cortex, basal ganglia, cerebellum, and brainstem function) will be implemented at the neural level (firing-rate, synaptic plasticity), and data obtained from the model will be compared to data from our collaborators and co-applicants. iii) Robotics: The models will be tested in simulation, and importantly, on a humanoid robot (iCub) in a real-world scenario resembling studies with humans. Although at its core our project is not a robotics project, but rather focused on model building and understanding biological principles of brain function, in the long run, the obtained results may lead to autonomous robots that possess the human-like neurocognitive architecture of a minimal self as an integral aspect of their behavior.

我们的项目提案以跨学科的方式解决了身体图式和机构(预测一个人自己行为的感觉后果)的共同发展。跨学科的组成部分是：i)理论/概念：基于来自人类研究的数据和基本的神经科学发现，我们开发了在大脑功能的神经系统水平上解释身体所有权和机构所需的整体机制的具体设计概念。这一概念模型指导了实验机构与我们的合作伙伴一起进一步评估该模型。Ii)计算神经科学方法：概念模型(代表顶叶皮质、基底节、小脑和脑干功能)将在神经层面(放电率、突触可塑性)实施，从该模型获得的数据将与我们的合作者和共同申请者的数据进行比较。3)机器人学：这些模型将在模拟中进行测试，重要的是，在一个类似于人类研究的真实世界场景中，在一个类人机器人(ICub)上进行测试。虽然我们的项目的核心不是机器人项目，而是专注于建立模型和理解大脑功能的生物学原理，但从长远来看，所获得的结果可能会导致自主机器人拥有类似人类的神经认知架构，将最小自我作为其行为的一个组成部分。