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: | Siamak Sorooshyari |
| Institution: | UC Berkeley |
| Department: | Integrative Biology |
| Country: | |
| Proposed Analysis: | Alterations in the brain’s connectivity or the interactions among brain regions as subjects age have been studied with the aid of resting state (rs)fMRI data attained from large numbers of healthy subjects of various demographics. This has been instrumental in providing insight into how fundamental phenotypes such as age affect the brain. Although machine learning (ML) techniques have already been deployed in such studies, in this work a novel question is presented and investigated. The belief that during healthy aging young brains have properties that are progressively similar to aged brains will be quantitatively scrutinized. The degree of the prospective monotonicity in the progression will be quantified, and variants of this brain age monotonicity hypothesis will also be presented. The work sheds light on the trajectory of functional connectivity (FC) during life in the effort of understanding the dynamics of brain aging. |
| Additional Investigators | |
| Investigator's Name: | Daniela Kaufer |
| Proposed Analysis: | Alterations in the brain’s connectivity or the interactions among brain regions as subjects age have been studied with the aid of resting state (rs)fMRI data attained from large numbers of healthy subjects of various demographics. This has been instrumental in providing insight into how fundamental phenotypes such as age affect the brain. Although machine learning (ML) techniques have already been deployed in such studies, in this work a novel question is presented and investigated. The belief that during healthy aging young brains have properties that are progressively similar to aged brains will be quantitatively scrutinized. The degree of the prospective monotonicity in the progression will be quantified, and variants of this brain age monotonicity hypothesis will also be presented. The work sheds light on the trajectory of functional connectivity (FC) during life in the effort of understanding the dynamics of brain aging. |
