Alleviating suffering for mental health patients

Neurobiologist Dr. Kafui Dzirasa is like a master auto mechanic for the brain. He studies the basic biological mechanisms of mental illness by observing how neural circuits function—or fail to function—in enabling different regions of the brain to communicate. By understanding these connections, Dzirasa devises biomedical innovations to reduce the suffering caused by mental illness. 

Neuroscientists often conduct research by studying one tiny brain region at a time. They might select a certain area of the brain based on past clues about its involvement in a given behavior, such as social behavior, and study that area in isolation. Dzirasa believes that looking at only one small brain region at a time is a mistake, so he takes the more holistic approach of a mechanic, studying how the assembled parts work together. 

“A car is not a steering wheel. A car is not tires. A car is not an engine. A car is not the speedometer. A car is not the headlights. You have to put them all together to get the car,” said Dzirasa, a physician-scientist who is the A. Eugene and Marie Washington Presidential Distinguished Professor of Psychiatry & Behavioral Sciences and Behavioral Medicine & Neurosciences. 

Dzirasa’s research has demonstrated the importance of crosstalk between brain regions and networks as the driver for depression and autism in mice. In 2022, he won a Pioneer Award from the National Institutes of Health—a five-year, $3.5 million grant he used to employ a new technology that improves communication across brain cells.  

The technology, called LinCx (long-term integration of circuits using connexins), delivers the unique protein connexin to brain cells. The connexin acts like a direct line for cells to talk with one another and better synchronize activity along circuits critical for mood and emotional regulation. Connexin comes from the white perch fish, which has these molecules attached between auditory nerve cells and tail-flip cells. This ultrafast neural connection helps the fish quickly escape when it hears an approaching predator. 

“We’re excited because we recently demonstrated this new connexin tool can modify brain circuits in worms and mice,” Dzirasa said, “so we’re hopeful that it can translate to humans.” 

To help assemble a clearer picture of his data, Dzirasa connected with his longtime collaborator David Carlson, an assistant professor of civil and environmental engineering and biostatistics and bioinformatics. Carlson is an expert in the field of machine learning, a branch of artificial intelligence whereby computers get better at understanding complex data the more they’re given. 

Carlson helped to develop a new AI system to make sense of the brain wave data. It analyzed electrical activity from every brain region—tens of thousands of brain cells. To gain precise control over these brain regions, the researchers used a light-based technique called optogenetics to enable them to instantly flick on specific brain regions at will. Lighting up prefrontal cortex brain cells provoked already outgoing mice to cozy up even more to another mouse, suggesting this social brain network both senses and directs social behavior. 

As a final test, Dzirasa asked whether this social brain network model could detect impaired social behavior in a mouse model of autism. When his team knocked out a gene implicated in people with autism, the mice’s behavior confounded the machine learning tool. It could no longer predict how social a given mouse was based on its brain waves, suggesting the new machine learning tool is good at detecting aberrant electrical activity. 

The research may lead to better diagnostic tools and even personalized repairs to get our brains running like finely tuned machines.