Leonardis Eric J, Breston Leo, Lucero-Moore Rhiannon, Sena Leigh, Kohli Raunit, Schuster Luisa, Barton-Gluzman Lacha, Quinn Laleh K, Wiles Janet, Chiba Andrea A
Department of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Program in Neurosciences, University of California, San Diego, San Diego, CA, United States.
Front Psychol. 2022 Aug 17;13:897603. doi: 10.3389/fpsyg.2022.897603. eCollection 2022.
Interactive neurorobotics is a subfield which characterizes brain responses evoked during interaction with a robot, and their relationship with the behavioral responses. Gathering rich neural and behavioral data from humans or animals responding to agents can act as a scaffold for the design process of future social robots. This research seeks to study how organisms respond to artificial agents in contrast to biological or inanimate ones. This experiment uses the novel affordances of the robotic platforms to investigate complex dynamics during minimally structured interactions that would be difficult to capture with classical experimental setups. We then propose a general framework for such experiments that emphasizes naturalistic interactions combined with multimodal observations and complementary analysis pipelines that are necessary to render a holistic picture of the data for the purpose of informing robotic design principles. Finally, we demonstrate this approach with an exemplar rat-robot social interaction task which included simultaneous multi-agent tracking and neural recordings.
交互式神经机器人技术是一个子领域，它描述了在与机器人交互过程中诱发的大脑反应及其与行为反应的关系。从人类或动物对智能体的反应中收集丰富的神经和行为数据，可以为未来社交机器人的设计过程提供支撑。本研究旨在探究生物体如何与人工智能体互动，以及与生物或无生命物体互动的差异。该实验利用机器人平台的新颖特性，研究在结构化程度极低的交互过程中的复杂动态，而这是传统实验装置难以捕捉的。然后，我们提出了一个此类实验的通用框架，强调自然主义交互与多模态观察以及互补分析管道相结合，这些对于全面呈现数据以指导机器人设计原则是必不可少的。最后，我们通过一个典型的大鼠 - 机器人社交互动任务展示了这种方法，该任务包括同步多智能体跟踪和神经记录。
