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Nearly 15 million American adults over the age of 18 suffer from depression reports the Anxiety and Depression Association of America Photo/iStock |
Yuxiao Yang, a Ph.D. candiate in electrical engineering, works to uncover the brain's mechanisms that underlie the country’s most common neurological disorders afflicting millions of patients, such as depression or Parkinson’s disease.
For example, 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.
The vision is to monitor a patient’s brain and analyze neural activity and signals to determine a person’s neurological disease state. The monitoring would be done through minimally-invasive electrodes to provide data of brain activity.
Doctors, scientists and engineers would then process the information based on the recorded activity to understand 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 electrical stimulation, we may be able to alleviate symptoms of the disease or even find out that the brain has the ability to heal itself,” Yang said.
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Yuxiao Yang Photo/USC Viterbi |
“One way for neurons to communicate is through electrical signals, like neural spiking activities,” Yang added. “Electrical stimulation, for example, may change the way neurons communicate. Correct stimulation may help alter chaotic neural communications in neurological disorders to help facilitate normal communications made in a healthy brain.”
This development, if successful, could supplement therapy and medication, especially in patients who are unresponsive to either and have no other treatment option available.
“We are in the early stages of thinking about whether electrical stimulation could be helpful and safe for patients as an alternative treatment,” said Maryam Shanechi, assistant professor in the Ming Hsieh Department of Electrical Engineering and Yang’s faculty adviser. "If the technology development is successful and safe, it may help treat neurological disorders for patients who do not respond to conventional therapies such as medication.”
“Our hope is stimulation can guide the brain to adapt itself towards a healthy state and finally heal itself and get rid of the need for stimulation," Yang said. "This will allow both doctors and scientists a better understanding of how the brain works and how the brain adapts and evolves in response to electrical stimulation."
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 control or unmanned drones, for example.
Yang has also applied control theory to induce anesthesia automatically; his technique would adjust the anesthetic drug infusion rate automatically and in real time, thus putting anesthesia induction on autopilot. His hope now is to develop controllers that adjust the electrical stimulation applied to the brain to help treat neurological diseases such as depression or Parkinson’s disease.
Currently, Yang is constructing brain models to see how neurological signals change in disease. He also uses data from the brain activity to determine the potential effects of electrical stimulation.
Yang estimates it will take about five years to develop a prototype device that could have potential for treatment and about 10 years for a finalized product.
“The main challenge with this work is that the brain mechanisms of varying diseases, such as Parkinson’s disease, 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 in 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.
