Statistical method for neural mechanism mediating and moderating cognitive system in Alzheimer's disease and aging research.

阿尔茨海默病(AD)以及正常衰老与多种脑部疾病有关 和认知变化。在研究认知变化时，已经观察到一些 人们比其他人能承受更多的大脑变化或病理，而这种差异 易感性与智商、教育程度、职业经历等指标有关。 观察是认知储备(CR)假说的基础，认知储备(CR)调节 大脑变化对认知的影响。医学成像的最新发展，特别是 多模式神经成像，可以更好地了解潜在的神经机制 认知变化和认知障碍的作用。然而，现有的统计方法并非如此。 专为容纳大规模多维数据而设计，尤其是为了 高维度的主持人和调解人。为了解决这些问题，我们建议开发， 验证并应用软件工具进行多通道的横截面和纵向分析 磁共振脑图像和从认知正常老化的个体获得的认知数据， 来自两项关于衰老和阿尔茨海默病的独立研究的临床前AD和AD： 参考能力神经网络(RANN)与阿尔茨海默病 神经成像倡议(ADNI)。我们将演示开发的统计方法提供 与当前工具相比，提高了准确性和稳健性。首先，我们将开发工具来识别 神经退行性变或病理标志物与脑功能之间的密切关系 (通过任务功能磁共振测量的网络表达)。第二, 我们将使用静息状态功能磁共振和任务功能磁共振获得CR的神经基质，然后 开发统计工具来测试成像CR代理的调节效果。第三，我们将 开发用于高维预测的稀疏调节调解方法和 调解人占温和的比例。测试认知任务中的网络表达是否 调节大脑变化(通过多模式结构磁共振测量)对认知的影响 表现、认知功能减退和痴呆症转变，以及衍生的神经是否 CR的底物调节中介作用。

Alzheimer's disease (AD), as well as normal aging, are associated with a wide range of brain and cognitive changes. In investigating cognitive changes, it has been observed that some people can sustain more brain changes or pathology than others, and this differential susceptibility is related to measures such as IQ, education, vocational experiences etc. This observation is the basis for the cognitive reserve (CR) hypothesis, where CR moderates the effects of brain changes on cognition. Recent developments in medical imaging, particularly multimodal neuroimaging, can provide better understanding of neural mechanisms that underlie both cognitive changes and the role of CR. However, existing statistical methods were not designed to accommodate large-scale multi-dimensional data, particularly for incorporating high-dimensional moderators and mediators. To address these issues, we propose to develop, validate, and apply software tools for the cross-sectional and longitudinal analysis of multimodal MR brain images and cognitive data acquired from individuals with normal cognitive aging, preclinical AD and AD from two independent studies of aging and Alzheimer's disease: the Reference Ability Neural Networks (RANN) (Yaakov Stern, PI) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). We will demonstrate that the developed statistical methods offer improved accuracy and robustness over current tools. First, we will develop tools for identifying robust relationships between neurodegeneration or pathology markers and brain function (network expression measured by task fMRI) in the presence of CR as a moderator. Second, we will derive neural substrate of CR using resting-state functional MRI and task fMRI and then develop statistical tools to test the moderation effect of the imaging CR proxies. Third, we will develop the sparse moderated mediation methods for high-dimensional predictors and mediators accounting for moderation. to test whether network expression during cognitive tasks mediates the effect of brain changes (measured via multimodal structural MRI) on cognitive performance, cognitive decline and dementia transition, and whether the derived neural substrate of CR moderates the mediation.