Christian Georg Habeck

The paper examines how resting-state brain signal variability relates to age, cognition, and cognitive reserve using neuroimaging data from 470 participants.

This study examines how amyloid-beta burden affects task-modulated brain connectivity during working memory retrieval and links these changes to task performance and cognitive resilience.

This study uses machine learning to show that integrating brain connectome data with amyloid-beta PET imaging improves prediction of cognitive decline in older adults.

The paper examines cf-mtDNA and GDF15 as potential biomarkers of mitochondrial health in aging, finding GDF15 correlates with age and diabetes while cf-mtDNA does not.

The paper examines immunosenescence trajectories in diverse populations, finding associations between immunological age and brain atrophy, while highlighting CMV status and genetic ancestry as key factors.

This study uses persistent homology-based functional connectivity to analyze resting-state brain networks and finds it better explains cognitive ability variance than traditional measures.

This paper develops a deep learning model to quantify cognitive reserve using structural MRI data from healthy cohorts and validates its generalizability across different populations and scanners using transfer learning.

This study examines age-related differences in cognitive abilities using fMRI and diffusion imaging, finding that vocabulary-related brain regions are better maintained with age than fluid abilities.

The paper identifies a task-invariant cognitive reserve network by analyzing functional connectivity changes during cognitive tasks and their correlation with IQ.

The paper investigates how low white matter microstructure in young adults correlates with white matter hyperintensities in older adults, finding that normatively low fractional anisotropy regions are more prone to damage.