Advancing Early Alzheimer's Detection Through Multimodal Neuroimaging Techniques

Alzheimer's Disease (AD) poses significant challenges in diagnosis and understanding its complex pathological mechanisms. With the advancements of multimodal neuroimaging approaches in cognitive neuroscience, researchers are now better equipped to unravel the organization and spatiotemporal dynamics of the human brain. Traditionally, AD research has often relied on single imaging modalities to investigate specific aspects of the disease, such as the mismatch between neurodegeneration and amyloid-β deposition in positron emission tomography (PET). However, recent studies have shown that integrating multiple neuroimaging modalities and biomarkers can provide a more comprehensive view of AD's complex pathology and mechanisms. Despite these advancements, there remains a critical need for further investigation to refine these techniques for early detection and greater diagnostic precision, as well as to develop effective clinical interventions.

This Research Topic aims to further refine multimodal neuroimaging techniques to achieve early detection of AD and greater AD diagnostic precision. Moreover, it intends to highlight innovative studies that leverage multimodal neuroimaging to advance our understanding of AD, with the ultimate goal of developing effective strategies to improve cognitive function in AD patients. This includes integrating cognitive behavioral therapy or brain stimulation interventions with neuroimaging. By combining insights from various imaging modalities, researchers can uncover novel understandings in AD pathogenesis and identify potential therapeutic targets.

To gather further insights into the boundaries of multimodal neuroimaging in AD, we welcome articles addressing, but not limited to, the following themes:
- Integrating PET and MRI for Early Diagnosis of Alzheimer's Disease
- Combining Functional and Structural Neuroimaging to Track Alzheimer's Disease Progression
- The Role of Multimodal Imaging in Unraveling Alzheimer's Disease Pathophysiology
- Multimodal Neuroimaging Biomarkers for Predicting Alzheimer's Disease Onset
- Multimodal Imaging Correlates of Neurodegeneration in Alzheimer's Disease
- Harnessing Multimodal Imaging for Alzheimer's Disease Therapeutic Development
- AI-Driven Integration of PET and MRI for Alzheimer's Disease Progression Analysis
- Modeling Disease Trajectory in Alzheimer's Patients with Combined Neuroimaging and Predictive Analytics
- Multimodal Imaging of Cognitive Resilience in Alzheimer's Disease
- Neuroimaging Insights into Factors of Cognitive Resilience in Alzheimer's Disease
- AI-Enhanced Multimodal Neuroimaging for Early Detection of Alzheimer's Disease