Alterations in Generalization Ability and Neuroimaging Markers with Respect to Aging and Alzheimer's Disease: A Comprehensive Meta-Analysis Dataset

Abstract: This dataset supports a comprehensive metadata analysis aimed at exploring emerging evidence for generalization deficits as a sensitive early measure of cognitive and neural decline in Alzheimer's disease (AD). It includes data on neuroimaging biomarkers, cognitive performance metrics related to generalization, and study-specific metadata extracted from multiple peer-reviewed publications. The data was curated and standardized to facilitate comparisons across studies, focusing on multimodal approaches to understanding aging and AD. This dataset serves as a resource for researchers investigating the interrelationships between generalization and neuroimaging, contributing to early AD diagnosis and interventions. It can be used for further meta-analyses, training predictive models, and hypothesis generation in aging and neuroimaging research.摘要： 本数据集支撑一项综合性元数据分析工作，旨在探索泛化缺陷（generalization deficits）作为阿尔茨海默病（Alzheimer's disease, AD）认知与神经衰退的敏感早期标志物的新兴证据。其涵盖神经影像生物标志物（neuroimaging biomarkers）、与泛化相关的认知表现指标，以及从多篇同行评议学术文献中提取的研究专属元数据。本数据集已完成整理与标准化处理，以促进跨研究间的对比分析，研究核心聚焦于解析衰老与阿尔茨海默病的多模态方法。本数据集可为探究泛化与神经影像之间内在关联的科研人员提供宝贵资源，助力阿尔茨海默病的早期诊断与干预研究。该数据集可应用于衰老与神经影像研究领域的进一步元分析（meta-analyses）、预测模型训练以及假说构建工作。