Alzheimer’s disease (AD) is one of the most common forms of dementia that has slowly negative impacts on memory and cognition. With the assistance of multimodal brain networks and graph-based analysis

NIAID Data Ecosystem30

Table_1_Predicting Brain Regions Related to Alzheimer's Disease Based on Global Feature.XLSX

阿尔茨海默病脑区识别

神经影像网络分析

Alzheimer's disease (AD) is a neurodegenerative disease that commonly affects the elderly; early diagnosis and timely treatment are very important to delay the course of the disease. In the past, most

NIAID Data Ecosystem20

Synaptic density affects clinical severity via network dysfunction in syndromes associated with Frontotemporal Lobar Degeneration

额颞叶变性

神经影像网络分析

Data used to derive figures and results in the primary manuscript and in the supplementary materials for Synaptic density affects clinical severity via network dysfunction in syndromes associated with

NIAID Data Ecosystem40

Peak voxels, cluster sizes (k), and t-values for encoding-related neural activity (encoding > baseline).

神经影像网络分析

记忆神经机制

Peak voxels were used to define ROIs for the multivariate analysis. DLPFC = dorsolateral prefrontal cortex; PrC = precuneus; ROI = region of interest.

NIAID Data Ecosystem20

Supplemental Data for Cerebral Oxygen Metabolic Stress, Microstructural Injury, and Infarction in Adults With Sickle Cell Disease

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