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: | Iva Brunec |
| Institution: | University of Toronto |
| Department: | Department of Psychology |
| Country: | |
| Proposed Analysis: | We propose to examine different signal properties along the hippocampal long axis as a potential indicator of pathological aging. In previous work examining resting state fMRI data of healthy controls, we found evidence that signal in the anterior hippocampus is significantly more autocorrelated over time, and has higher voxelwise similarity than that in the posterior hippocampus. This is thought to correspond to representational granularity, such that the posterior hippocampus supports more fine-grained representations that change more rapidly from moment to moment. We hypothesize that a decrease in, or absence of, this anteroposterior distinction may be indicative of a risk of developing Alzheimer’s disease as it would reflect a loss of coding precision in neural signal, related to memory decline. Further, we propose to examine the connectivity between the anterior and posterior hippocampi and other brain regions, as the coherence of the whole-brain networks within which hippocampal subregions act as hubs may be increasingly compromised with disease severity. Access to ADNI data would provide an ideal avenue to test this hypothesis and enable us to characterize changes in fMRI signal, indicative of Alzheimer’s disease. As our method of investigating signal similarity across voxels and across time is quick and cost-effective, we believe it may complement traditional methods of assessment. |
| Additional Investigators |
