Understanding cognitive function across the adult lifespan: structure-function interactions in the aging brain.
Description: Given a worldwide ageing population, cognitive change through the lifespan is a topic of urgent international scientific and social concern. To promote cognitive health in old age, we require a better understanding of how brain structure and function support cognitive performance. Aging has a pronounced impact on both the structure (loss of neurons and connections) and function of the brain. Nevertheless, in most studies, brain measures explain only a small part of the variance in cognitive scores, and the literature contains many contradictory findings. To further our understanding of brain-cognition relationships in aging, a new approach is required, which incorporates the complex interdependence between brain function and brain structure. Changes in gray and white matter affect local activity as well as activity and connectivity in more distant brain regions. That is why the relation between brain function and cognition in old age cannot be fully understood until individual variations in brain structure are taken into account. The proposed work will use a unique, large-scale dataset, from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) that includes extensive measures of cognitive function, white matter, gray matter and brain activity as measured by functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). A combination of hypothesis and data-driven analysis techniques will be used to examine the complex associations between structure, function and cognition across the lifespan. I will i) examine the interaction between structure and function within the context of short-term memory and inhibitory control, ii) examine within-person brain activity and connectivity determinants of cognitive performance, and iii) implement novel methods for combining data across modalities. These analyses will help unravel structure-function interactions in the aging brain, and their implications for cognitive functioning. The insights gained by this approach will aid the development of interventions to maintain cognitive health in an aging population.
Funding type: fellowship
Funder scheme: NWO-Talentprogramma Veni 2016 MaGW Veni
Start date: 2017-01-01
End date: 2021-09-08
Investigator: Linda Geerligs
Institution: Universiteit van Amsterdam
Funded outputs count: 10
Funder award ID: 451-16-013
OpenAlex ID: G4798037546