Development of a Mobile Cognitive App for Detecting and Monitoring Change in Preclinical Alzheimer's Disease

项目摘要/摘要 阿尔茨海默病及相关痴呆患者认知症状的诊断与监测 需要对认知变化进行有效和可靠的评估。传统测试中的当前限制 衡量标准包括测试时间长短、参与度低、日常可变性、数据点少以及 识别有认知衰退风险的正常个体的细微差异的能力。目前的许多 可用的计算机化评估工具(1)尚未更新，以纳入当前的认知 神经科学理论(2)没有针对与大脑最早的神经解剖学变化相关的措施 老化和神经退行性变和/或(3)没有利用数字技术的好处来最大化有效 和可靠的认知数据收集。检测脑内微小认知变化的灵敏移动测量方法 临床前阿尔茨海默病(AD)及其分子病理学和生物标记物的研究 神经退行性疾病将结合起来确定哪些人将从干预中受益最多。这个项目将 包括开发和验证两个、引人入胜、用户友好和基于经验的认知评估 任务，并创建移动认知应用性能平台(MCAPP)。这两项认知测试将 包括：(1)包括相似对象对的存储卡游戏(已经设计和试点测试) 以及(2)使用代码进行执行功能和处理速度测试 完成游戏。认知测试将包括高天花板和低下限，以捕捉一系列能力，爆裂 测试以提高数据的可靠性，游戏化设计以提高参与度和积极性，以及移动性- 基于设计，可在所有环境中捕获数据。MCAPP将在一个具有良好特征的 宾夕法尼亚阿尔茨海默病中心认知正常的老年人队列。这群人将 同时完成神经心理电池、高分辨率结构磁共振和淀粉样蛋白PET成像 通过资助的P32和R01项目，在本研究中将利用这些项目来了解 认知表现和神经影像生物标记物状态之间的关系。结构成像目标将包括 内侧颞叶的区域与临床前阿尔茨海默病的早期阶段有关。这个 MCAPP的目的是收集可靠和有效的认知数据，以发现AD相关的非常早期的迹象 认知变化和远程跟踪对干预措施的反应。远程管理，引人入胜的认知 对AD风险个体的最早变化敏感的测试有可能扩大我们的 对衰老过程中的认知知识，导致早期发现认知变异性，监测随时间的变化，以及 由于干预而产生的变化。该项目将促进数据收集，以支持与 早期职业首席调查员在ADRD研究中的MCAPP和职业发展机会。

PROJECT SUMMARY/ABSTRACT The diagnosis and monitoring of cognitive symptoms in Alzheimer's disease and related dementias (ADRD) requires valid and reliable assessment of cognitive change. Current limitations in traditionally used testing measures include the length of testing, low engagement, day-to day variability, few data points, and limits in the ability to identify subtle differences in normal individuals at risk for cognitive decline. Many of the currently available computerized assessment tools either (1) have not been updated to incorporate current cognitive neuroscience theory (2) do not target measures associated with the earliest neuroanatomical changes in brain aging and neurodegeneration and/or (3) do not capitalize on the benefits of digital technology to maximize valid and reliable cognitive data collection. Mobile and sensitive measures for detection of subtle cognitive change in preclinical Alzheimer's Disease (AD) along with biomarker measures of molecular pathology and neurodegeneration will combine to identify individuals who will benefit most from interventions. This project will include development and validation of two, engaging, user-friendly and empirically based cognitive assessment tasks and create the Mobile Cognitive App Performance Platform (mCAPP). The two cognitive tests will comprise: (1) a memory card game (already designed and pilot-tested) that includes similar pairs of objects and increasing memory load and (2) an executive functioning and processing speed test using a code completion game. The cognitive tests will include a high-ceiling and low floor to capture a range of ability, burst testing to increase reliability of the data, gamified design to increase engagement and motivation, and mobile- based design for capturing data in all environments. The mCAPP will be validated in a well-characterized cohort of older adults with normal cognition in the Penn Alzheimer's Disease Center. The cohort will concurrently complete a neuropsychological battery, high resolution structural MRI and amyloid PET imaging through funded P32 and R01 projects, which will be leveraged in this study to understand the relationships between cognitive performance and neuroimaging biomarker status. Structural imaging targets will include areas of the medial temporal lobe implicated in the earliest stages of preclinical Alzheimer's disease. The purpose of the mCAPP is to collect reliable and valid cognitive data to detect very early signs of AD-related cognitive change and remotely track response to interventions. Remotely administered, engaging cognitive tests that are sensitive to the earliest changes in individuals at risk for AD have the potential to expand our knowledge of cognition in aging, lead to early detection of cognitive variability, monitor change over time and change as a result of intervention. This project will facilitate collection of data to support larger studies with the mCAPP and career development opportunities in ADRD research for the early career principal investigator.