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: | Matthew Hyett |
| Institution: | University of Western Australia |
| Department: | Psychological Science |
| Country: | |
| Proposed Analysis: | The proposed analyses aims to examine resting-state network similarities and differences between those diagnosed with MCI, AD, and midlife and later life major depressive disorder. I am a member of a multicentric resting-state fMRI consortium (PsyMRI) led by Professor Martin Walter at the University of Tubingen in Germany, comprising individuals with established MDD, MCI, and AD (and healthy controls). I have pre-processed rs-fMRI data from 10 of the 20 sites from PsyMRI using FSL tools (modelling site differences with the FSL FIX tool), and am looking to increase the sample size in the MCI and AD groups (and older matched healthy controls) hence the request to access ADNI data. The proposed analysis, incorporating PsyMRI and ADNI data, will include 1) group ICA across all subjects, 2) identification of salience, executive control, and default mode networks from the ICA (as well as additional resting state networks such as attention control networks), 3) dual regression on ICA modes to obtain single-subject timeseries for each network, 4) single-subject spectral dynamic causal modelling (implemented in SPM) to estimate influences between and within modes, 5) parametric empirical Bayes (PEB; also implemented in SPM) to identify similarities and differences between groups (MDD, MCI, AD, HC). An additional "inverted" analysis (i.e., without reference to clinical diagnostic category) will be conducted separate to the above analysis - this will be achieved through a single subject prediction approach. Dynamic causal models will be estimated (again between ICA components) for each individual, and the parameters of these models will be used to predict "disease states", the hypothesis being that a common brain network will link midlife MDD with MCI and AD. These analyses will be performed under the guidance of colleague (and former primary PhD supervisor), Professor Michael Breakspear. |
| Additional Investigators | |
| Investigator's Name: | Michael Breakspear |
| Proposed Analysis: | See Proposed Analysis under PI Matthew Hyett. |
| Investigator's Name: | Michael Weinborn |
| Proposed Analysis: | See Proposed Analysis under PI Matthew Hyett. |
| Investigator's Name: | Brandon Gavett |
| Proposed Analysis: | See Proposed Analysis under PI Matthew Hyett. |
