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Shown on the left, is a graphical visualization of a Bayesian computational model used for estimating risk functions for mild cognitive impairment, which is shown on the right. Credit: Zita Oravecz

Co-hire Zita Oravecz leads $3.1M study on early signs, diagnosis of Alzheimer’s disease

Zita Oravecz, associate professor of human development and family studies in the Penn State College of Health and Human Development, is leading a four-year, $3,148,346 National Institute of Aging (NIA)-funded study that aims to use computational models and psychology to detect early signs of Alzheimer’s disease and related dementias (ADRD) that may appear approximately 20 years before an official diagnosis.

Oravecz, who is a Penn State Institute for Computational and Data Sciences (ICDS) co-hire, is part of a team of researchers that includes co-investigators Jonathan Hakun, assistant professor of neurology, Penn State College of Medicine; Martin Sliwinski, professor of human development and family studies and director of the Penn State Center for Healthy Aging; and John Felt, assistant research professor, Center for Healthy Aging. Sharon Kim, a graduate student in the Department of Human Development and Family Studies at Penn State, will also work on this study.

The team will look for subtle cognitive changes in participants aged 40 to 65 through a smartphone-based study, using an app developed by the Center for Healthy Aging. Participants will complete surveys and “brain games’ on their phones, in their natural environment multiple times each day for two weeks at a time. The games include matching of complex symbols and remembering the location of dots on a grid.

The researchers aim to disentangle the processes underlying cognitive change and individual differences by using Bayesian models. The team will use ICDS’ Roar to develop the models.

“The research could open up this kind of testing, in a way, society-wide,” Oravecz said. “Once we have our methods developed, we can monitor progress over time spans of years with these new methods … how cognition changes, including disease progression and normative aging. We will be able to establish a risk score, and clinicians can then decide how they act on it.”

Read the full Penn State News story here…

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