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: | Kaileigh Bunting |
| Institution: | Cognitive Neuroscience of Schizophrenia Lab |
| Department: | Faculty of Medicine, Psychiatry |
| Country: | |
| Proposed Analysis: | We plan to analyze the data with Constrained Principal Component Analysis (CPCA), which combines regression analysis and principal component analysis into a unified framework. fMRI-CPCA uses CPCA to analyze fMRI data, and derives images of functional functional networks from singular value decomposition of BOLD signal time series with the analyzed variance constrained to that which is predictable from stimulus timing and other constraints. Constraining the analyzed BOLD signal variance allows derivation of functional networks that change activation in peristimulus time, using non-peristimulus time scans as a baseline. fMRICPCA can also be thought of as deconvolution PCA. CPCA allows: 1. Determination of multiple functional networks involved in a task. 2. Estimation of the pattern of BOLD changes associated with each functional network over peristimulus time points. 3. Quantification of the degree of interaction between these multiple functional networks. 4. A statistical test of the reliability of components, and the degree to which experimental manipulations affect each functional network. |
| Additional Investigators |
