AI-powered Surreal-GAN identifies diverse brain aging patterns

The aging human brain undergoes many structural changes that vary based on genetics, an individual’s lifestyle, and the presence of coexisting diseases. This heterogeneity in brain aging is also influenced by factors that can either exacerbate or protect against age-related neuropathological processes. Early and subtle changes in specific brain regions can emerge during the preclinical phases of neurodegenerative diseases like Alzheimer’s disease. Therefore, it is crucial to understand these neuroanatomical changes across a broad spectrum of individuals. Traditional neuroimaging studies have provided important insights into the role of aging and diseases in altering brain structure and function, often relying on case-control comparisons. However, these methods are limited in their ability to address individual heterogeneity, as they typically focus on average patterns, rather than capturing the diverse neuroanatomical changes across individuals.