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: | Sidi Wu |
| Institution: | Simon Fraser University |
| Department: | Statistics and Actuarial Science |
| Country: | |
| Proposed Analysis: | The analysis is concerning the functional data analysis(FDA) of longitudinal resting-state fMRI (rs-fMRI) data. The goal of the study is to relate resting-state effective brain connectivity to biological characteristics and genetic markers for different default mode networks (DMN). We consider networks comprised of four (DMN4 - 16 connections) and six (DMN6 - 36 connections) core regions of the DMN. The networks will be estimated using spectral dynamic causal modelling (DCM) and the networks include self-connections and directed connections for and between all of the regions associated with each resting-state network. For all networks considered, a sequence of effective connectivity networks for each subject with each network corresponding to one of the longitudinal rs-fMRI scans for that subject and representing effective connectivity will be estimated based on the scans. We account for within-subject clustering in networks using function-on-scalar regression. Functional-on-scalar model considers digest the effect of time on effective connectivities by regarding the network edges as the functions of time and allows the association with a given biological feature or genetic marker to vary longitudinally. With a comparison between different functional regression models, we are expecting to capture statistical evidences to reveal the associations between resting-state effective connectivity networks to biological characteristics and genetic markers at different networks. |
| Additional Investigators |
