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: | Dilmini Wijesinghe |
| Institution: | USC Stevens Neuroimaging and Informatics Institute |
| Department: | USC Stevens Neuroimaging and Informatics Institute |
| Country: | |
| Proposed Analysis: | I am a new postdoctoral fellow in Dr. Jann's lab at INI working complexity measures in rs-fMRI data. This work is part of his NIA funded R01 The goal of this project is to further develop our Complexity Toolbox and a cloud-based pipeline for comprehensive complexity analysis of (large scale) fMRI data. We will systematically evaluate the complexity of fMRI as a novel imaging marker of AD populations, using the Alzheimer's Disease Neuroimaging Initiative (ADNI-3). Finally, we will use advanced machine learning techniques to evaluate complexity of rs-fMRI as a predictor for transversion from healthy to MCI and to AD. We will generate a disease staging model based on multimodal AD biomarkers including PET, CSF and rs-fMRI measures |
| Additional Investigators | |
| Investigator's Name: | Kay Jann |
| Proposed Analysis: | The goal of this project is to further develop our Complexity Toolbox and a cloud-based pipeline for comprehensive complexity analysis of (large scale) fMRI data. We will systematically evaluate the complexity of fMRI as a novel imaging marker of AD in LOAD populations, using rs-fMRI and PET data from Alzheimer's Disease Neuroimaging Initiative (ADNI-3). Finally, we will use advanced machine learning techniques to evaluate complexity of rs-fMRI as a predictor for transversion from healthy to MCI and to AD. We will generate a disease staging model based on multimodal AD biomarkers including PET, CSF and rs-fMRI measures |
