Engineering, ArtSci researchers will use fMRI and twins to better understand cognitive control
From the WashU Newsroom…
How our brains process information is intimately tied to the kinds of goals we have or the tasks we need to perform. For example, when showed the word “yellow,” our brains process it differently depending on whether we are asked to read the word or report the color of the ink. Not only that, each of us processes information differently, making understanding the brain basis of these kinds of complex cognitive processes particularly challenging for scientists.
ShiNung Ching, assistant professor in the Preston M. Green Department of Electrical & Systems Science in the School of Engineering & Applied Science, and Todd Braver, professor of psychological & brain sciences in Arts & Sciences, both at Washington University in St. Louis, will create new models of brain function to tease apart those individual differences and create new models for them with a three-year, $610,560 grant from the National Science Foundation (NSF).
Matthew Singh, a neuroscience graduate student, is another member of the research team.
The grant is one of 18 awarded by the NSF to conduct innovative research on neural and cognitive systems and will contribute to the NSF’s commitment to the National Institutes of Health’s Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative.
“The teams will integrate multiple disciplines to look at fundamental questions about the brain in new ways,” said Shubhra Gangopadhyay, NSF program director in the Engineering Directorate. “The research will tackle problems that were previously intractable for neuroscience and cognitive science and will open up new avenues for future research. We are excited to see where these high-risk, high-reward proposals take us as a field.”
The research seeks to understand the mechanisms of cognitive control, or how the brain functions to allow us to vary our information processing and behavior based on our current goals and the situational context, such as not eating a friend’s lunch despite being hungry.
Ching and Braver will study two sets of data to determine these mechanisms. One set is the functional MRI (fMRI) data from the Human Connectome Project (HCP), a five-year, National Institutes of Health-sponsored study led by Washington University School of Medicine in St. Louis, aimed at constructing a complete map of structural and functional neural connections in the brains of a large, representative sample of individuals and their relatives.
Unlike traditional MRI, which takes anatomical images of the brain, fMRI measures brain activity by analyzing the neurons’ demand for oxygen in the blood — the more activity, the more oxygen is needed. The initial stage of model building, which Singh has carried out, has used the HCP data to develop and evaluate the accuracy of the models in recreating the time course of brain activity patterns, sometimes called dynamics.
Next, the researchers will deploy the models to understand brain dynamics in a second set of fMRI data that had individuals engage in a wide range of tasks that specifically depended on cognitive control. In the example of viewing words printed in different colors of ink, it requires more cognitive control when the task is to name the ink color and ignore the word itself.