There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Zhang Xinyi |
| Institution: | Zhejiang University |
| Department: | Neurology |
| Country: | |
| Proposed Analysis: | The objectively-defined subtle cognitive decline (Obj-SCD) individuals had higher progression rates of cognitive decline and pathological deposition than healthy elderly, indicating its higher risk of progressing to AD. However, little is known about the functional alterations during this stage. To cover this gap, we included 42 cognitive normal (CN), 29 objectively-defined subtle cognitive decline (Obj-SCD) and 55 mild cognitive impairment (MCI) subjects based on neuropsychological measures from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Thirty CN, 22 Obj-SCD and 48 MCI had longitudinal MR data. We calculated degree centrality (DC) and eigenvector centrality (EC) for each participant by using resting-state functional MRI. For cross-sectional data, analysis of covariance (ANCOVA) was performed to detect between-group differences of DC and EC after controlling age, sex, and education. For longitudinal data, repeated measurement ANCOVA were used for comparing the alterations during follow-up period among three groups. In order to classify the clinical significance, we correlated DC and EC value to AD biomarkers and cognitive function. |
| Additional Investigators |
