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: | Hanwen Bi |
| Institution: | Columbia University |
| Department: | Biomedical Engineering |
| Country: | |
| Proposed Analysis: | fMRI is a powerful tool to observe brain and help us to understand brain function. On a large scale, understanding brain function can direct doctors to the biological cause of psychological disorder, like which part of the brain is mal-functioning. However, it is difficult to detect intrinsic structured patterns (functional brain networks) directly from raw resting state fMRI (rs-fMRI) data. For final project of BMEN E4000 course, we are going to build a variational autoencoder (VAE) to uncover the latent pattern of rs-fMRI and it should allow us to connect behaviors with the brain areas easily. |
| Additional Investigators | |
| Investigator's Name: | Yiwen Tian |
| Proposed Analysis: | fMRI is a powerful tool to observe brain and help us to understand brain function. On a large scale, understanding brain function can direct doctors to the biological cause of psychological disorder, like which part of the brain is mal-functioning. However, it is difficult to detect intrinsic structured patterns (functional brain networks) directly from raw resting state fMRI (rs-fMRI) data. For final project of BMEN E4000 course, we are going to build a variational autoencoder (VAE) to uncover the latent pattern of rs-fMRI and it should allow us to connect behaviors with the brain areas easily. |
