ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Zhengjun Zhang |
| Institution: | University of Wisconsin |
| Department: | Statistics |
| Country: | |
| Proposed Analysis: | We are going to use tail quotient correlation coefficients (TQCC) and generalized measures of correlation (GMC) to study hidden functional connectivity among localized regions of pixels. TQCC has been successfully applied to climate image analysis. TQCC (and NQCC) is a nonlinear dependence measure, which is particularly useful for detecting rare event, i.e. rare diseases. Using GMC, a possible directed network graphs may be constructed. We are going to compare hidden functional connectivity from images diagnosed with Alzheimer’s disease and hidden functional connectivity from images not yet diagnosed with Alzheimer’s disease or in progress. There is a chance to discover important connectivity associated with rare diseases. |
| Additional Investigators |
