USC Viterbi researcher experiments with electrical stimulation to study the country’s most common mental condition
Depression, a mental disorder that is far more than just general sadness, saps the emotion and enjoyment out of daily activities and hobbies, derails motivation, keeps people tossing and turning at nights and leaves millions of Americans in constant despair.
According to the American Psychological Association, depression is the most common mental condition in America, and 80 percent of those who have it experience a relapse at some point. The Anxiety and Depression Association of America reports major depressive disorder affects approximately 14.8 million American adults, or about 6.7 percent of the U.S. population over the age of 18, in a given year.
Yuxiao Yang, a PhD candidate in electrical engineering at the USC Viterbi School of Engineering, is experimenting with electrical stimulation to rework the brain to better monitor depression and other neurological disorders.
How it works
The process involves implanting a chip into the patient’s brain, which would analyze neural activity and signals to determine a person’s mental and emotional state. This chip is connected to recording electrode arrays that contact brain cells and provide data of brain activity.
After doctors, scientists and engineers digitally process the information, they can conclude how the patient’s brain is operating at specific times and circumstances while building their knowledge of how they can stimulate the brain to treat these diseases.
“Through this electrical stimulation, the brain may have the ability to change its structure to make new connections,” Yang said.
One way for neurons to communicate is through electrical signals, like neural spiking activities.
Yuxiao Yang
“One way for neurons to communicate is through electrical signals, like neural spiking activities,” Yang added. “Electrical stimulation can change the way neurons communicate. Correct stimulation can alter chaotic neural communications in depression to help facilitate normal communications made in a healthy brain.”
This development could supplement therapy and medicine, especially in patients who are unresponsive to either.
Antidepressants on the rise
Specifically, this could have a profound impact on antidepressants, as over-prescription has become pervasive in America. In 2011, the National Center for Health Statistics, found the rate of antidepressant use in this country among teens and adults — people age 12 and older — has increased by almost 400 percent between 1988-1994 and 2005-08.
In fact, The Journal of Clinical Psychiatry reports 10.4 percent of Americans currently take antidepressants, compared to just 6.5 percent in 1999.
“Right now, this technology is invasive, but it can help people who are unresponsive to medicine or psychotherapy,” said Maryam Shanechi, assistant professor in the Ming Hsieh Department of Electrical Engineering and Yang’s faculty adviser. “Once it becomes more developed, it can be available to more patients to help treat their disorders outside of conventional ways.”
According to Yang, “Our hope is stimulation can guide the brain to adapt itself to a healthy state and finally heal itself and get rid of the need for stimulation. This will allow both doctors and scientists a better understanding of how the brain works and how the brain adapts and evolves to external stimulation.”
Taking control
Yang’s research is based on control theory, where a controller determines the inputs into a system to control its actions. This is already applied to aircraft, as unmanned drones are directed from people operating them from a control center.
Currently, Yang is constructing brain models to see how neurological signals are affected by engineering. He also uses data from the brain activity of primates and rodents to determine the potential effects of electrical stimulation.
Yang estimates it will take about five years to develop a prototype device that could potentially treat depression and about 10 years for a finalized product.
“The main challenge with this project is the mechanisms of varying diseases in the brain are poorly understood,” Shanechi said. “We will have to run a system identification, which will demonstrate how the brain works. Once we have a greater understanding, finding out how to cure diseases will be easier.”
Yang lists understanding the brain’s synapse signals, properly identifying brain signals with certain diseases, predicting the patient’s behavior, and developing safe and compatible devices as the biggest challenges ahead.
“The brain is the most mysterious computer in the world,” he said.
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