Building a shared infrastructure for cognitive assessment in the service of cognitive training research

构建认知评估共享基础设施，服务于认知训练研究

• 批准号: 10817565
• 负责人: JOAQUIN A ANGUERA
• 金额: $ 14.5万
• 依托单位: NORTHEASTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-05 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10817565
• 关键词: Building; shared; infrastructure; cognitive; assessment

Effective measurement of cognitive abilities is fundamental to effective diagnostics, risk assessment and evaluation of interventions targeted towards older adults (OA) and in particular those with Alzheimer's Disease and related dementias (ADRD). With the ubiquitous availability of smartphone/tablet technology in modern society a proliferation of mobile cognitive assessments from companies, healthcare providers, and researchers are being developed. However, a difficulty in evaluating such interventions, and in particular making comparison between them is the lack of standardization/interoperability of assessment tools. This is especially the case for early stage/mechanistic studies where it is common for investigators to each use their own labs' toolset to evaluate intervention outcomes. Here we address particular needs in the field of cognitive training, as well as for other longitudinal assessments focused on OA, where the limited standardization and accessibility of cognitive outcome measures makes it difficult to evaluate effectiveness of interventions. This R21/R33 infrastructure proposal seeks to develop shared tools to facilitate effective translation and sharing of cognitive assessment and training procedures. We accomplish this by leveraging technologies, existing assessment batteries, and know- how from 3 groups that have each independently developed robust systems for cognitive assessment and training that can run on mobile devices (UCR Brain Game Center, UCSF Neuroscape Center, and UCI Working Memory and Plasticity Lab). We target development of systems that allow for interoperability of assessments, enrollment/participant tracking systems, data visualization, and participant compliance systems. In the R21 phase, we aim to develop such systems and demonstrate that they can be effectively shared across labs, and in the R33 phase, these systems will be both tested for robustness in large scale-research projects that will now be able to share outcome measures, and for developing personalized, precision training approaches for participants based upon these assessments. Further, these systems will be documented and will be shared with other scientists groups to reduce the barrier of entry for other groups. The long-term impact of this work will be an infrastructure that will support better comparison across studies of cognitive training, as well as other interventions that are increasingly being used to ameliorate cognitive declines in older adults such as those related to ADRD. The key value of this system compared to others is that it will simultaneously support the flexibility required for basic research, by facilitating groups to continue to use their own lab's software systems, while at the same time providing them with a powerful infrastructure for sharing that allows them to incorporate assessments, server infrastructure and compliance tools into their own studies. This will facilitate comparisons across studies using common outcome measures as well as the ability to use the same assessments in numerous other domains including risk-assessment and longitudinal testing in older adults at risk for ADRD.

有效的认知能力测量是有效诊断、风险评估和 针对老年人，特别是阿尔茨海默病患者的干预措施的评价 和相关痴呆症(ADRD)。随着现代智能手机/平板电脑技术的无处不在 来自公司、医疗保健提供商和研究人员的移动认知评估激增 正在开发中。然而，在评估这种干预措施，特别是进行比较方面存在困难 其间是评估工具缺乏标准化/互操作性。这种情况尤其适用于 早期/机械性研究，研究人员通常使用自己的实验室工具集来 评估干预结果。在这里，我们解决认知培训领域的特殊需求，以及 其他纵向评估侧重于办公自动化，其中认知的标准化和可获得性有限 结果衡量标准使评估干预措施的有效性变得困难。此R21/R33基础架构 提案旨在开发共享工具，以促进认知评估和共享的有效翻译和共享 培训程序。我们通过利用技术、现有评估电池和知识来实现这一点- 如何从3个小组各自独立开发出强大的认知评估系统和 可在移动设备上运行的培训(UCR Brain Game Center、UCSF Neuroscape Center和UCI Working 记忆与可塑性实验室)。我们的目标是开发能够实现评估互操作性的系统， 注册/参与者跟踪系统、数据可视化和参与者合规系统。在R21 在这个阶段，我们的目标是开发这样的系统，并证明它们可以有效地在实验室之间共享，以及 在R33阶段，这些系统都将在大型研究项目中进行健壮性测试，现在将 能够分享成果衡量标准，并为以下方面开发个性化、精准的培训方法 参与者基于这些评估。此外，这些系统将被记录下来，并将与 其他科学家小组旨在降低其他群体的进入门槛。这项工作的长期影响将是 基础设施将支持认知训练以及其他研究之间更好的比较 越来越多的干预措施被用来改善老年人的认知衰退，比如 与ADRD有关。与其他系统相比，该系统的关键价值在于它将同时支持 基础研究所需的灵活性，通过促进团队继续使用自己实验室的软件系统， 同时为他们提供强大的共享基础设施，使他们能够 将评估、服务器基础架构和合规工具整合到自己的研究中。这将有助于比较 跨研究使用共同的结果衡量标准以及使用相同评估的能力 许多其他领域，包括风险评估和对有ADRD风险的老年人进行纵向测试。

项目成果

Leveraging technology to personalize cognitive enhancement methods in aging.

• DOI: 10.1038/s43587-022-00237-5
• 发表时间: 2022-06
• 期刊: NATURE AGING
• 作者: Ziegler, David A.;Anguera, Joaquin A.;Gallen, Courtney L.;Hsu, Wan-Yu;Wais, Peter E.;Gazzaley, Adam
• 通讯作者: Gazzaley, Adam