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: | Zachery Morrissey |
| Institution: | University of Illinois at Chicago |
| Department: | Psychiatry |
| Country: | |
| Proposed Analysis: | Our study proposes to use a comparative neuroimaging approach using data from human healthy aging, MCI, and AD patients with transgenic mouse models of AD. The aim of this study is to examine molecular mechanisms that may be involved in connectome-level changes that are observed in human AD neuroimaging data, as well as how environmental enrichment in mouse models may translate to improved cognition. To that end, we will be computing the structural and functional connectome from human DTI and resting-state fMRI data, respectively. We will be analyzing graph theory network measures and hierarchical modularity. In addition, we aim to apply functional network analysis methods we recently developed to map functional connectivity gradient changes across disease groups and compare to mouse functional connectivity. Finally, we aim to perform fiber tract analyses to compare human phenotype changes in white matter structures to those observed in transgenic AD mouse phenotype across age. |
| Additional Investigators | |
| Investigator's Name: | Liang Zhan |
| Proposed Analysis: | This study will use a comparative approach to study neuroimaging data from healthy aging, MCI, and AD neuroimaging data along with transgenic mouse models of AD. This study aims to investigate the molecular mechanisms that may underly connectome-level changes in AD, as well as the role that environmental enrichment may have in improving cognition. Structural and functional connectomes will be computed from DTI and resting-state fMRI data, respectively. Graph theory network measures and hierarchical modularity will be analyzed. Additionally, we will be using a method we recently developed to map functional connectivity gradient changes across disease groups. Finally, we aim to study white matter tract changes to compare human and mouse phenotype across disease conditions for translational analysis. |
| Investigator's Name: | Alex Leow |
| Proposed Analysis: | This study will use a comparative approach to study neuroimaging data from healthy aging, MCI, and AD neuroimaging data along with transgenic mouse models of AD. This study aims to investigate the molecular mechanisms that may underly connectome-level changes in AD, as well as the role that environmental enrichment may have in improving cognition. Structural and functional connectomes will be computed from DTI and resting-state fMRI data, respectively. Graph theory network measures and hierarchical modularity will be analyzed. Additionally, we will be using a method we recently developed to map functional connectivity gradient changes across disease groups. Finally, we aim to study white matter tract changes to compare human and mouse phenotype across disease conditions for translational analysis. |
