Grant: CIHR Fellowship

As one of the most prevalent pathologies in a rapidly aging population, Alzheimer's disease (AD) has become one of the biggest healthcare and societal burdens. AD affects the brain decades before symptoms emerge. As such, cognitive neuroscientists have been attempting to better understand its neurobiological substrates. Clinical tools such as MRI offer tractable, non-invasive access to AD neuropathology at the earliest disease stages, when individuals do not show symptoms but are at high risk of converting to AD (pre-symptomatic). Traditional MRI analysis methods, however, have been limiting our insight into AD's early causes. Such methods have been ignoring brain properties that are fundamental to healthy brain function, and structures where AD may originate, based on existing work. In this proposal, we want to uncover the role that these neglected brain properties and structures may be playing in the emergence of AD pathology. To do so, we are bringing a new multi-disciplinary perspective to the study of early AD that focuses on these traditionally ignored, but crucial, brain features. First, we will use empirical high quality MRI data on pre-symptomatic older adults to quantify alterations in these brain features. Second, we will integrate these empirical measures within an optimized mathematical model of brain function that will allow us to simulate early AD stages in a controlled setting. Taken together, this work will make significant scientific and translational contributions by identifying the neural mechanisms that cause AD emergence. With this knowledge, we can inform early detection strategies and develop more precise interventions before AD symptoms occur.