Lateral inhibition is when certain neurons suppress the activity of their neighboring neurons. Imagine an artist drawing, darkening the lines around the contours, highlighting the boundaries between objects and space, or objects and other objects. Comparably, in the visual system, lateral inhibition sharpens the contrast between different visual stimuli.

“This research is really getting at how our visual system not only highlights important things, but also actively suppresses irrelevant information in the background,” said lead researcher Bilal Haider, associate professor in the Wallace H. Coulter Department of Biomedical Engineering. “That ability to filter out distractions is crucial.”

Understanding how these inhibitory mechanisms work could provide insights into why people have trouble filtering out distractions or focusing on what’s important, in conditions like autism or ADHD.

“Our findings may also influence how we design artificial intelligence and neural networks,” said Haider, whose team published its work this month in Nature Neuroscience. “Current AI systems treat all the computing units the same, but the brain has figured out how to assign specialized computing roles.”

Joseph Del Rosario, a former graduate student in the Haider lab, was the lead author. Another key contributor was Hannah Choi, assistant professor in the School of Mathematics, and her Research Group in Mathematical Neuroscience. Their team built computational models to test the biological findings.

“Collaborating with mathematicians to really understand the computational principles underlying these inhibitory processes is a great example of how neuroscience can inform fields like AI,” Haider said.

Read more in the Coulter Department of Biomedical Engineering newsroom.