Ching, Raman team up to study sensory networks in the brain

ShiNung Ching and Barani Raman are bringing together their expertise on brain networks to take a closer look at how the various networks in the brain operate.

Barani Raman and his team trained locusts to recognize odors to learn more about how the brain processes stimuli.
The team, both in the School of Engineering & Applied Science, received a two-year, $80,000 grant from the McDonnell Center for Systems Neuroscience at Washington University School of Medicine for the project, which begins July 1.

Raman, an associate professor in the Department of Biomedical Engineering, studies how chemosensory signals are received and processed in relatively simple brains of locusts. Ching, an assistant professor in the Department of Electrical & Systems Engineering, will use Raman’s data to develop some general theories on the types of computations occurring in a locust’s brain as it processes the odors.

“This work is a nice synergy of neural engineering, neuroscience and systems science,” Ching says. “We think there is some really good potential here for sustained cross-disciplinary impact.”

Ching and Raman seek to determine how brain networks allow us to resolve ambiguity in environmental stimuli. For example, if one is presented with the odors of lemon and rose — both strong, unambiguous odors on their own — how do the brain’s networks allow one to determine if the odors are separate or mixed and resolve the ambiguity?

“We don’t know yet how the brain supports that kind of perceptual reasoning,” Ching says. “The idea of this work is to think about what structures might exist in the brain at a basic neurophysiological level that can help this kind of resolution occur.”

“We are interested in studying simple detection and response to sensory stimuli that are a mixture of attractive and aversive components,” Raman says.

Raman’s team will give the locusts brief and prolonged odor puffs of a variety of odors to determine how the neural responses drive the final behavioral output. Understanding the set of rules that governs how a sensory input is encoded by neural networks to facilitate eliciting a particular behavior response is not fully understood.

“Our work with the behavioral tasks aims to bridge this gap and is expected to reveal how odorants are processed in natural environments with multiple competing stimulus sources,” Raman says.

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