Toward strengthening learning of neurocognitive skills via biofeedback for Veterans with brain injury

脑损伤可以深刻地改变一个人的生活轨迹。通常情况下，困难与 在引导认知和情绪的多个方面以最佳方式服务于当前目标方面的缺陷，特别是在 挑战的设定。许多经历过脑损伤的9/11后退伍军人可能会从学习中受益 在朝着个人目标努力的同时，更好地调节他们潜在的认知-情绪状态的技能。 然而，学习如何在最需要的时候战略性和灵活地应用州监管技能(SR) 在日常生活中是具有挑战性的。 为了解决这个问题，我们以前设计和开发了数字场景来帮助技能学习； 情景作为系统的学习机会，在广泛的认知挑战中练习SRS 同时还提供个性化的数据驱动反馈，以指导学习过程。在这个新的 项目，我们寻求通过利用反映潜在因素的生理数据来进一步加强对SRS的学习 在训练场景中，大脑状态作为个性化的生物反馈。为学员(退伍军人)提供访问 他们潜在的大脑状态的其他方面(例如，大脑网络活动)可以增强 退伍军人学习自我管理的技能。总而言之，将SRS应用于多个和 伴随着生物反馈的各种认知挑战有可能加速和加强有效性 技能学习。 有脑损伤病史(21-60岁)的9-11后退伍军人将被招募参加这一项目。参与者 将执行一系列计算机化的认知挑战任务，同时具有其中央和 周围神经生理学监测。这些调查的初步目标是确定潜在的 通过探索指示大脑状态变化的生物统计变量，为生物反馈提供有用的培训目标 认知挑战以及SRS的应用。根据这些结果，我们将试行反馈模型 设计、开发并集成到数字场景中。参与者将参与设计和 通过提供用户对反馈的重要性、易用性和 能够利用反馈来调整培训目标。 从这个项目中获得的知识将有助于技能闭环系统的开发 脑损伤后的训练。在该系统中，反馈的多个加强层(行为表现、 技能使用、神经生理学和自我报告的数据)将集中起来，帮助退伍军人学习如何最好地使用这些 改善他们日常功能的技能。这样的系统也将是一个宝贵的工具，帮助当地和 远程康复。

Brain injury can alter an individual’s life trajectory in profound ways. Quite frequently, difficulties are related to deficits in directing multiple aspects of cognition and emotion to optimally serve a current goal, especially in the setting of challenges. Many post-9/11 Veterans who have experienced a brain injury may benefit from learning skills to better regulate their underlying cognitive-emotional state while working toward their personal goals. However, learning how to apply state regulation skills (SRS) strategically and flexibly when they are most needed in everyday life is challenging. In order to address this issue, we previously designed and developed digital scenarios to assist with skill learning; scenarios function as systematic learning opportunities to practice SRS in a wide range of cognitively challenging contexts while also providing individualized data-driven feedback to guide the learning process. In this new project, we seek to further strengthen learning of SRS by utilizing physiological data reflective of underlying brain state as individualized biofeedback during training scenarios. Providing learners (Veterans) access to aspects of their underlying brain state that are otherwise inaccessible (e.g., brain network activity) can empower Veterans to learn skills for self-regulation. Taken together, intensive practice with applying SRS to multiple and varied cognitive challenges accompanied by biofeedback has the potential to accelerate and strengthen effective skill learning. Post 9-11 Veterans with a history of TBI (age 21-60) will be recruited for participation in this project. Participants will perform a series of computerized cognitive challenge tasks while having aspects of their central and peripheral neurophysiology monitored. The preliminary objective of these investigations is to identify potentially useful training targets for biofeedback by exploring biometric variables that index changes in brain state with cognitive challenges as well as application of SRS. Based upon these results, pilot feedback models we will designed, developed, and integrated into digital scenarios. Participants will contribute to the design and implementation process by providing user-feedback on factors such as salience of feedback, ease-of-use, and ability to utilize feedback to moderate the training target. The knowledge gained from this project will help inform the development of a closed-loop system for skill training following brain injury. In this system, multiple reinforcing layers of feedback (behavioral performance, data on skill use, neurophysiology, and self-report) will converge to help Veterans learn how to best use these skills to improve their everyday functioning. Such a system also will be a valuable tool to assist with local and remote rehabilitation.