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: | Jinglong Chen |
| Institution: | Guangzhou First People's Hospital ,South China University of Technology |
| Department: | Geriatric Department |
| Country: | |
| Proposed Analysis: | We plan to divide MCI patients into slow progressing MCI subgroup(SP-MCI) and rapid progressing MCI subgroup(RP-MCI), then evaluate grey matter volume using voxel-based morphometry in T1-weighted images, white matter diffusion using tract-based spatial statistics (TBSS) in DTI images, and region-to-network functional connectivity in rest-state functional MRI images using FSL and dual regression in both groups,compare the difference of clinical presentation, serum biomarkers and parameters of structural and functional MRI images between groups,then establish a deep learning model to determine rapid progressing MCI subgroup.Then based on the model,we plan to recruit SP-MCI patients in our unit to explore whether repetitive transcranial magnetic stimulation(rTMs) could delay SP-MCI patients developing into dementia. In our clinical practise of treating cognitive impaired patients by rTMs,We found some right-handed patients benefiting from stimulating right DFPLC rather than left DFPLC.So,We wonder whether there is difference of structural and functional connectivity of left DFPLC and right DFPLC.We intend to use ADNI database,compare the structural and functional brain networks related to the left DFPLC and the right DFPLC in MCI and dementia patients, to determine whether there are differences in the functional connections of white matter fiber bundles and brain networks related to cognition in the left and right cerebral hemispheres. |
| Additional Investigators | |
| Investigator's Name: | Xiaoqi Yu |
| Proposed Analysis: | to evaluate grey matter volume using voxel-based morphometry(VBM) in T1-weighted images, white matter diffusion using tract-based spatial statistics (TBSS) in DTI images in MCI and dementia patients. |
| Investigator's Name: | Qing Li |
| Proposed Analysis: | To establish a deep learning model to determine rapid progressing MCI subgroup,with clinical presentation,cognitive scale, serum biomarkers and parameters of structural and functional MRI images |
