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: | Behnaz Jafari |
| Institution: | University of Calgary |
| Department: | Biomedical Engineering |
| Country: | |
| Proposed Analysis: | Objectives/Hypothesis Developing a deep learning model to improve the accuracy of Alzheimer's detection using fMRI and EEG data. 2.1 Specific Aim 1 To construct a graph neural network to estimate fMRI-based effective connectivity using linear/ non-linear Granger causality method for each brain regions for healthy control and Alzheimer's. 2.2 Specific Aim 2 To fit a RNN (e.g., LSTM) to EEG data for both healthy control and Alzheimer's 2.3 Specific Aim 3 To develop a neural network-based framework for integrating EEG and fMRI timeseries data. 2.4 Specific Aim 4 Application to data from healthy controls and Alzheimer's |
| Additional Investigators | |
| Investigator's Name: | Roberto Sotero Diaz |
| Proposed Analysis: | Objectives/Hypothesis Developing a deep learning model to improve the accuracy of Alzheimer's detection using fMRI and EEG data. 2.1 Specific Aim 1 To construct a graph neural network to estimate fMRI-based effective connectivity using linear/ non-linear Granger causality method for each brain regions for healthy control and Alzheimer's. 2.2 Specific Aim 2 To fit a RNN (e.g., LSTM) to EEG data for both healthy control and Alzheimer's 2.3 Specific Aim 3 To develop a neural network-based framework for integrating EEG and fMRI timeseries data. 2.4 Specific Aim 4 Application to data from healthy controls and Alzheimer's |
