back to news Aug. 18, 2015

Psychology Professor to Share in $13.1 million NSF BRAIN Initiative

Zhong-Lin Lu, professor of psychology and director of the Center for Cognitive and Behavioral Brain Imaging and the Center for Cognitive Science, is one of a handful of research scientists across the U.S. selected to share $13.1 million for 16 new awards that are part of NSF’s support for integrative, fundamental brain research and the BRAIN initiative. Lu and his colleague, Mark Steyvers, professor of cognitive sciences, University of California, Irvine, will apply a new modeling framework that integrates brain imaging with individuals’ behavior information — a new approach that could revolutionize the field of cognitive neuroscience.

Their research project, “Understanding individual differences in cognitive performance: Joint hierarchical Bayesian modeling of behavioral and neuroimaging data,” will explore a mathematical and computational framework for investigating a large-sample neuroimaging and behavioral dataset to improve our understanding of individual differences in cognitive performance.

“Our goal is to predict individual cognitive performance in novel, real-world situations based on observed behavioral and neuroimaging data and contribute to the understanding of cognitive health and wellbeing of individuals,” said Lu.

The technical approach will build on and integrate recent advances in cognitive science, neuroscience, statistics, and machine learning. Statistical models will integrate data from both brain imaging and behavioral tests to generate predictions that otherwise may not be possible with a single source of data. The research will go beyond establishing and explaining individual differences to predicting individual cognitive performance in a variety of tasks.

Lu’s work aligns with Translational Data Analytics, one of the investment areas in Ohio State’s Discovery Themes initiative. This focus area centers on answering today’s complex challenges with problem-solving through data analytics, decision science and public-private collaborations, transforming how the university co-develops data-enriched solutions with the external community.

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