EAGER: Advancing Human-Cyber Interaction: Development of Neuro-Physiological Methods

该项目旨在改善人类，特别是那些认知能力退化或有限的人，与复杂计算或计算机支持的服务（广义上称为网络系统）的互动方式。为了提高用户界面（UI）的状态并创建更具适应性的交互模式，有关人机交互（HCI）的基础知识必须包含更多的神经生理学证据。 该项目提出了实现这一进步的三步计划。首先，将仔细选择并招募三个实验受试者组进行比较分析：1）健康和年轻成人，2）痴呆或接近痴呆的老年人，以及3）患有轻度脑外伤的成人。第二，实验会话将基于需要在MRI机器内执行任务的递增复杂信息搜索和消息传递任务进行。实验阶段的目标是使用fMRI收集神经元激活模式，以及与响应时间和准确性相关的行为数据。 第三，将分析实验结果，以建立神经元证据，行为和UI性能之间的潜在关联。 该计划的广泛技术目标是建立和完善在复杂HCI条件下收集神经生理学证据的方法，并开发新的用户建模技术，以支持灵活有效的交互。 开发能够监测和确定与即将发生或现有脑退行性疾病相关的风险因素的高级用户界面是一个长期的转化目标。所产生的资源和成果将在计算机和信息科学学科的学者中广泛共享，旨在促进和支持下一代HCI研究人员的培训。

The project aims to improve how humans, particularly those with degenerative cognitive conditions or limited cognitive capacities, interact with complex computing or computer-enabled services (broadly called cyber-systems). To advance the state of user interfaces (UI) and create more adaptive interaction modalities, the foundational knowledge regarding human-cyber interaction (HCI) must incorporate more neuro-physiological evidence. The project proposes a three-step plan for attaining this advance. First, three experimental subject groups will be carefully selected and recruited for comparative analysis: 1) healthy and young adults 2) demented or near-demented older adults, and 3) adults suffering from mild brain trauma. Second, experimental sessions will be conducted based on incrementally complex information searching and messaging tasks that require executing the tasks inside an MRI machine. The goal of the experimental phase is to collect neuronal activation patterns using fMRI, as well as behavioral data associated with response time and accuracy. Third, the experimental findings will be analyzed to establish potential association among neuronal evidence, behavior, and UI performance. The broad technical aim of the initiative is to establish and refine methods for gathering neuro-physiological evidence under complex HCI conditions, and develop new user modeling techniques for supporting flexible and effective interaction. Development of advanced user interfaces capable of monitoring and establishing risk factors associated with impending or existing brain-degenerative conditions is a longer term translational aim. The resources and outcomes produced will be broadly shared among scholars in computer and information science disciplines, with the aim of promoting and supporting training of next-generation HCI researchers.