The human brain, composed of about 86 billion noisy neurons, is a reliable, durable, complex, and cryptic biological supercomputer. A community of multidisciplinary researchers at Georgia Tech is decrypting that neuronal chatter, which may hold the key to better treatments for disease and addiction, advanced robotics and artificial intelligence (AI), and even global energy efficiency.

These researchers work in the realm of computational neuroscience, a branch of neuroscience that uses mathematical models, computer simulations, and theoretical analysis of the brain to gain a deeper understanding of the nervous system.

"We want to understand the brain and the important data that we gather from this amazing, mysterious organ,” said Chethan Pandarinath, assistant professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. “But for a long time, we really didn’t have the adequate tools.”

Basically, the ability to look at the brain and gather large amounts of data from it has advanced rapidly — faster than our ability to understand it all.

“There has been an explosion of technology over the past five or 10 years,” Pandarinath said. “So, we’re moving into a different space in the ways we approach the brain, and the ways we think about it.”

Pandarinath and fellow Coulter Department faculty members Eva Dyer and Chris Rozell are profiled, along with several other Georgia Tech researchers working in computational neuroscience, this week. 

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