This research project aims to investigate how aging affects brain function and its connection to neurodegenerative diseases like Alzheimer’s. We will use a method called canonical correlation analysis (CCA) to analyze data from the UK Biobank, which contains rich information on both brain imaging and behavioral characteristics of participants.
The scientific rationale behind this project lies in the fact that aging and neurodegenerative diseases often exhibit the change of brain connectivity patterns. Aging is commonly associated with declines in cognitive and behavioral functions, and uncovering the relationship between these changes and brain connectivity patterns can inform interventions to support healthy aging. Additionally, by understanding what happens during “normal aging” compared to “pathological aging”, we hope to establish reference points that can help differentiate between normal aging and pathological conditions like Alzheimer’s.
This project will span 36 months to thoroughly analyze the complex data collected from the UK Biobank. By leveraging the extensive dataset and employing advanced analytical techniques like CCA, we aim to uncover novel insights into the neural mechanisms underlying aging and neurodegenerative diseases.
The public health impact of this research could be significant. By better understanding the normal and pathological aging process at the level of brain connectivity, we can improve early detection and intervention strategies for neurodegenerative diseases. This could lead to more effective treatments and interventions to support healthy aging and reduce the burden of age-related cognitive decline on individuals and healthcare systems. Ultimately, the findings from this project have the potential to contribute to improved public health outcomes and quality of life for older adults.