Early diagnosis of Alzheimer's disease and monitoring of disease progression require the investigation of different potential biomarkers, including structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), cerebrospinal fluid (CSF) and positron emission tomography (PET). This project uses resting state functional MR images to differentiate healthy patients from those at risk for developing Alzheimer's disease. During a resting state fMRI scan a patient lies inside an MR scanner for about 10 minutes and performs no task. About every 2 seconds, a functional MR image is acquired which, at the end of the scan, results in a 3D movie showing activity of the resting brain.

Different areas of the brain show a degree of coherence in their resting state signals that closely resembles the functional connectivity found using task based experiments. Our goal is to find characteristics in the brain connectivity obtained from resting state fMRI scans that make it possible to predict, years before the first symptoms become apparent, whether a person will develop Alzheimer's disease or not.