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WashU engineer developing methods to model, analyze brain networks

Adapting tools from a toolbox traditionally used to study and design mechanical or electrical systems, an engineer at Washington University in St. Louis seeks to analyze how information is processed in the brain.

ShiNung Ching, PhD
ShiNung Ching

ShiNung Ching, assistant professor of electrical & systems engineering in the School of Engineering & Applied Science, will use a three-year, $374,643 grant from the National Science Foundation to develop and analyze mathematical models of brain networks. Specifically, Ching will use these models to investigate how particular features of brain networks may enable processing of information, such as sounds and visual cues from the environment.

"We're developing new instantiations of engineering theory to study biological networks and understand how biology has engineered the brain to perform its functions," Ching said. "In much the same way that we would analyze a mechanical system, such as an airplane or a power grid, we're using these formal engineering methods to study networks in the brain."

While man-made systems are relatively straightforward, the brain has unparalleled complexity, Ching said, making such work a challenge. To address this challenge, he plans to take what is known about the brain's anatomy and develop mathematical descriptions of neurons and networks. From there, he can extract key features to develop simpler models for analysis.

"We try to simplify a system that is in fact nearly intractable into representative models that are more accessible," he said. "Our strategy is to break down the complexities of neural circuits into smaller units to use as building blocks for the larger system."

In addition to the research, Ching plans to host high school students from a local magnet school as summer interns to learn how engineering can reveal scientific insights in untraditional areas.

The School of Engineering & Applied Science at Washington University in St. Louis focuses intellectual efforts through a new convergence paradigm and builds on strengths, particularly as applied to medicine and health, energy and environment, entrepreneurship and security. With 88 tenured/tenure-track and 40 additional full-time faculty, 1,300 undergraduate students, more than 900 graduate students and more than 23,000 alumni, we are working to leverage our partnerships with academic and industry partners — across disciplines and across the world — to contribute to solving the greatest global challenges of the 21st century.

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"In much the same way that we would analyze a mechanical system, such as an airplane or a power grid, we're using these formal engineering methods to study networks in the brain."