MRI-based characterization of subgroups in aging and dementia
SNF Mobility fellowship awarded to Dr. Ahmed Abdulkadir
Neurodegenerative disorders threaten the mental health of elderly people. The rate of loss of neurons and its effect on the cognitive capacity varies considerably across individuals.
This project aims to improve our understanding of the interplay between cognitive performance and biological measures, obtained from non-invasive brain imaging, which, eventually, will result in more accurate prognoses.
Neurodegenerative disorders, including Alzheimer's disease, are characterized by clinical symptoms and their underlying biological characteristics. Clinical symptoms include memory problems or difficulties in spatial orientation. Biological characteristics include, for instance, size and shape of certain brain regions or the concentration of certain protein aggregates in the cerebro-spinal fluid. Clinical symptoms are most relevant for the patients and their relatives, whereas biological signs often appear earlier. The interplay between the biology (cause) and cognition (effect) is complex and heterogeneous. This project aims at studying the heterogeneity in the population. To cover a wide spectrum of the population, we will pool and analyze data from multiple data bases. Established statistical methods, machine learning, and deep learning are combined to obtain novel insights. The results will be presented and discussed in publicly available research articles. This will contribute to a better understanding of healthy aging as well as effects of neurodegenerative disorders on individual clinical profiles. The findings will help to improve the selection of patients for clinical studies and, thanks to more accurate prognosis, eventually will benefit patients, relatives, and caregivers.