Within-person dynamics of cognition and personality in healthy aging and Alzheimer's disease.

项目摘要/摘要 阿尔茨海默病(AD)的干预研究需要准确测量以下各项的认知功能 很多年了。认知可能会显著波动的事实阻碍了对功能的充分描述 从时刻到时刻，从一天到一天。这一额外的方差增加了测量噪声， 降低检测干预效果的敏感度。然而，与其将认知可变性归因于 测量误差，有越来越多的证据表明，性能的波动反映了 有意义的生理和心理过程，包括日常情绪、动机和注意力的变化。 这些心理机制中的许多都可以通过对人格的标准评估来捕捉，这 已被证明是AD风险的重要行为预测因子。该项目的总体目标是应用 密集的纵向研究技术，以分析认知功能，以便描述和解释 健康老龄化和有轻度或可疑认知障碍的个体的表现变异性。如果 认知的日常变化预示着后来的认知能力下降或其他有临床意义的结果，它说 在临床试验中作为额外或替代的认知终点可能是有用的。这项提案旨在适用于 采用动态结构方程模型(DSEM)进行为期三周的密集纵向研究设计。DSEM 模型允许对变异性进行直接和可靠的统计评估，将其作为关键晚年生活的敏感标志 结果包括认知能力下降和进展为阿尔茨海默病。我会收集日常的认知和 心理(例如，人格)功能对健康老年人和有 有问题的损害。DSEM将检验这一假设，即人内认知差异与 临床状态。对现有数据集的重新分析将通过以下方式进一步验证此方法 认知变异性对疾病进展和体内AD生物标志物的影响。 我将通过以下方式补充我测量健康老龄化和早期AD认知的丰富经验 另外，高级分析技术方面的教学培训，包括贝叶斯建模和动力学 结构方程模型，强调密集的纵向研究设计。此外，我还将收获 提供临床功能评估和判断痴呆症的存在/严重程度的经验。这个 约书亚·杰克逊博士和约翰·莫里斯博士被选为本次申请的导师，是国际公认的 健康老龄化的人格评估和纵向建模领域的专家，以及临床领域的专家 分别对AD进行评估，并非常适合担任该项目的导师。 通过本申请中描述的培训和研究计划，我将为 广告研究。这项建议开发的技术可以很容易地推广到其他神经退行性疾病或 认知起关键作用的临床障碍。

Project Abstract / Summary Intervention studies of Alzheimer disease (AD) require accurate measurement of cognitive function across many years. Adequate description of function is hampered by the fact that cognition can significantly fluctuate from moment-to-moment and from day-to-day. This additional variance adds measurement noise which impairs sensitivity to detect intervention effects. However, rather than ascribing cognitive variability to measurement error, there is accumulating evidence to suggest that fluctuations in performance are reflective of meaningful biological and psychological processes, including variations in daily mood, motivation and attention. Many of these psychological mechanisms can be captured via standard assessments of personality, which have been shown to be important behavioral predictors of AD risk. The overall goal of this project is to apply intensive longitudinal research techniques to the analysis of cognitive function in order to describe and explain performance variability in healthy aging and in individuals with mild or questionable cognitive impairment. If daily variability in cognition is predictive of later cognitive decline or other clinically meaningful outcomes, it may be useful as an additional or alternative cognitive endpoint in clinical trials. This proposal aims to apply dynamic structural equation models (DSEM) to a three-week intensive longitudinal research design. DSEM models allow for direct and robust statistical evaluation of variability as a sensitive marker of critical late life outcomes including cognitive decline and progression to AD. I will collect daily measures of cognitive and psychological (e.g., personality) function for a three-week period on healthy older adults and those with questionable impairment. DSEM will test the hypothesis that within-person variability in cognition is related to clinical status. Reanalysis of an existing dataset will provide further validation of this approach by relating cognitive variability to disease progression and in vivo AD biomarkers. I will supplement my extensive experience measuring cognition in healthy aging and early stage AD by gaining additional, didactic training in advanced analytical techniques including Bayesian modeling and dynamic structural equation modeling with emphasis on intensive longitudinal research designs. In addition, I will gain experience providing assessments of clinical function and judging the presence / severity of dementia. The mentors selected for this application, Drs. Joshua Jackson and John Morris are internationally recognized experts in the fields of personality assessment and longitudinal modeling in healthy aging, and clinical assessment of AD respectively and are well suited to serve as mentors on this project. Through the training and research plan described in this application, I will produce new cognitive endpoints for AD research. Techniques developed in this proposal can be readily extended to other neurodegenerative or clinical disorders where cognition plays a key role.