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: | Si Gao |
| Institution: | Maryland Psychiatric Research Center |
| Department: | Department of Psychiatry |
| Country: | |
| Proposed Analysis: | Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. We propose to use ADNI dataset to evaluate the Regional Vulnerability Index (RVI) that was developed to quantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We would like to evaluate the sensitivity and specificity of the RVI approach for major depressive (MDD) and anxiety disorders (AD) in the data collected by IDA by evaluating the change in similarity to these illnesses with the change in diagnostic status, cognitive measurements and symptoms of depression and anxiety. |
| Additional Investigators | |
| Investigator's Name: | Peter Kochunov |
| Proposed Analysis: | Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. We propose to use ADNI dataset to evaluate the Regional Vulnerability Index (RVI) that was developed to quantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We would like to evaluate the sensitivity and specificity of the RVI approach for major depressive (MDD) and anxiety disorders (AD) in the data collected by IDA by evaluating the change in similarity to these illnesses with the change in diagnostic status, cognitive measurements and symptoms of depression and anxiety. |
| Investigator's Name: | Zhenyao Ye |
| Proposed Analysis: | Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. We propose to use ADNI dataset to evaluate the Regional Vulnerability Index (RVI) that was developed to quantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We would like to evaluate the sensitivity and specificity of the RVI approach for major depressive (MDD) and anxiety disorders (AD) in the data collected by IDA by evaluating the change in similarity to these illnesses with the change in diagnostic status, cognitive measurements and symptoms of depression and anxiety. |
