HCC: Small: Investigating the temporal dynamics of resilience during human-computer interaction: an EEG-fNIRS study

HCC：小：研究人机交互过程中弹性的时间动态：一项 EEG-fNIRS 研究

• 批准号: 2232869
• 负责人: Joseph Nuamah
• 金额: $ 23.01万
• 依托单位: Oklahoma State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2232869&HistoricalAwards=false
• 关键词: HCC; Small; Investigating; temporal; dynamics

Many people spend part of the day in stressful conditions, which are known in general to be a major contributor to burnout, diminished productivity, and numerous other health risks, whereas some people (including for example air traffic controllers, soldiers, and first responders) work in high stress environments seemingly with no ill effects. Why certain individuals perform better under high stress than others with similar training remains unexplored. Resilience, the ability to maintain performance during stressful events, is a crucial attribute of healthy individuals who work in such environments. Because resilience has important implications for human well-being and task performance, there is a need to identify healthy individuals who are vulnerable to stress-related performance decline, preferably prior to actual performance under stress, to facilitate delivery of focused intervention that might help prevent the development of clinical stress disorders that pose a tremendous burden both for the individual and for society in general. This project will fundamentally advance our understanding of stress resilience by addressing the limitations of existing stress resilience measures and identifying potential biomarkers of stress resilience. Project outcomes will contribute to the assessment of the capabilities of healthy individuals who must maintain performance in the face of escalating cognitive demands such as emergency room personnel and first responders, prediction of their expected variation over time, and applicant suitability of recruitment for occupations within challenging operating environments.The objective of this research is to identify neural signatures, and to develop predictive models of task performance using neurophysiological features of dynamic resilience. This work will utilize hybrid EEG-fNIRS and community detection techniques to track brain organization during human-computer interaction under stress. Combining both EEG and fNIRS has great potential to provide deeper insight into stress resilience than either modality could alone. The dynamic functional connectivity approach employed in this study will likely provide insight into neural processes underlying resilience, while the dynamic network measures identified may serve as potential biomarkers for stress resilience. This project will not only enhance scientific knowledge on the relationship between temporal dynamics of resilience and neural adaptations but will also provide novel dynamic resilience biomarkers that may be used to determine the limits of human performance in high-stakes occupational settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

许多人在一天中的一部分时间都花在压力的条件下，这通常是导致倦怠，生产力降低以及许多其他健康风险的主要贡献者，而某些人（包括空中交通管制员，士兵和急救人员）在高压力环境中工作似乎没有任何影响。为什么某些人在高压力下的表现要比其他类似训练的人表现更好。韧性，在压力事件中保持表现的能力是在这种环境中工作的健康个体的关键属性。由于弹性对人类的福祉和任务表现具有重要意义，因此有必要确定那些容易受到压力相关的绩效下降的健康个体，最好是在压力下实际表现之前，以促进聚焦干预措施的提供，这可能有助于防止临床应激障碍的发展，这些临床应激障碍对个人和整个社会造成了巨大的负担。该项目从根本上可以通过解决现有的压力弹性措施的局限性并确定潜在的压力弹性生物标志物，从根本上提高我们对压力弹性的理解。 Project outcomes will contribute to the assessment of the capabilities of healthy individuals who must maintain performance in the face of escalating cognitive demands such as emergency room personnel and first responders, prediction of their expected variation over time, and applicant suitability of recruitment for occupations within challenging operating environments.The objective of this research is to identify neural signatures, and to develop predictive models of task performance using neurophysiological features of dynamic resilience.这项工作将利用混合EEG-FNIRS和社区检测技术在压力下的人类计算机相互作用期间跟踪大脑组织。与单独的模式相比，将脑电图和FNIRS结合起来，可以更深入地了解压力弹性。本研究中采用的动态功能连通性方法可能会提供对弹性背后的神经过程的见解，而所确定的动态网络测量可能是应激弹性的潜在生物标志物。 This project will not only enhance scientific knowledge on the relationship between temporal dynamics of resilience and neural adaptations but will also provide novel dynamic resilience biomarkers that may be used to determine the limits of human performance in high-stakes occupational settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.