Identifying Five Dominant Dimensions of Neurodegeneration in Brain Aging through Deep Learning: Correlations with Clinical and Genetic Measures
Zhijian Yang, Junhao Wen, Guray Erus, Christos Davatzikos, the iSTAGING consortium · 2025
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Description
Zhijian Yang and co-authors, working with a large consortium, published a study in 2025 that sorts brain aging into five main patterns. Brains do not all age the same way, and lumping every change together hides who is at risk for what. The team used a deep learning method to pull distinct patterns out of a huge set of scans.
They drew on nearly fifty thousand people across eleven studies, with scans, health data, and gene data. The five patterns cover shrinkage in deep areas, memory areas, and several parts of the cortex. People with dementia scored high on some patterns, while other illnesses mapped onto others. The scheme gives aging research a shared vocabulary.
Catalog record
| CREATOR | Zhijian Yang, Junhao Wen, Guray Erus, Christos Davatzikos, the iSTAGING consortium |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |