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Brain, Meet Machine

Top 35 Global Innovator: Assistant Professor Maryam Shanechi included in 2014 MIT TR35 for work in brain-machine interfaces
By: Katie McKissick
August 19, 2014 —
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Assistant Professor Maryam Shanechi

“I work at the interface of electrical engineering and neuroscience, both to understand brain function and to develop effective treatments for neurological diseases,” said Maryam Shanechi, a new assistant professor in the Ming Hsieh Department of Electrical Engineering. “In particular, I work at the interface of systems theory, signal processing and neuroscience to develop brain-machine interfaces.”

Her work earned her recognition in the 2014 "MIT Technology Review" TR35: the top 35 innovators under the age of 35. This annual list recognizes young talent whose work has great potential to transform the world. Shanechi will be joining the ranks of previously recognized innovators like Larry Page, Mark Zuckerberg and eight fellow USC Viterbi faculty, including two additional honorees on this year's list.

What does Shanechi research about brain-machine interfaces?

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There are two functions for a brain-machine interface: outward control and inward control. In the former, the brain machine-interface allows the brain to directly control an external device such as a prosthetic arm. In the latter, it controls the internal state of the brain. Shanechi has developed brain-machine interfaces of both types.

To help paralyzed patients or amputees, brain-machine interfaces record the activity of neurons in the brain and use that information to control a device. In the future this will allow paralyzed patients to pick up a pencil with a prosthetic hand by simply thinking about it—the same way able-bodied people use their own appendages.

Shanechi has developed these brain-machine interfaces not only for control of external devices but also for control of one’s own arm. Earlier this year, Shanechi published a paper in "Nature Communications" on a brain-machine interface that controlled the arm of a sedated primate. This sleeping primate served as a model for a paralyzed arm, and another primate moved the “paralyzed” primate’s arm purely with its thoughts. This work created a lot of excitement and media attention.

The brain-machine interface is not just for controlling external devices, though. It can be applied toward controlling the internal state of the brain itself. This could be used to treat diseases like Parkinson’s and neuropsychiatric disorders, such as depression and PTSD, in which misfiring neurons lead to devastating health conditions. 

How would it work? The brain-machine interface would record the electrical activity of the brain, and then apply electrical stimulation to calm the irregular neuronal activity that causes these debilitating conditions. Shanechi develops control algorithms that will make this system work in real time: interpreting the current state of the brain and deciding exactly how much stimulation to apply to remedy any problems. Shanechi also develops brain-machine interfaces for automatic anesthetic drug delivery that interpret how anesthetized the brain is based on its activity and control the drug infusion rate accordingly.

Moving prosthetics with your mind and treating complex neurological diseases with brain implants may sound like engineering dreams that won’t be realized for many decades, but it could be far sooner than that, says Shanechi.

“With the advent of the Obama BRAIN Initiative and the emphasis that’s placed on the interface of technology and neuroscience in order to treat brain disorders, we are hoping to make a lot of progress in the next five to 10 years.”

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Illustration by Esther Yoon

As a graduate student, Shanechi started off by working in information theory and wireless communication. She chose her current research focus—the intersection of engineering and neuroscience—by reflecting on how she could apply her skills in control theory and signal processing to have direct impact on people’s lives.

“I realized that I could use the same engineering principles to decode a brain signal instead of a wireless signal, to understand the brain and treat its disorders, and to directly impact the lives of millions of patients. That’s what motivates me and gets me really excited.”

At USC Viterbi, Shanechi will continue her work on control-theoretic algorithm development for these brain-machine interfaces and on the study of the neural basis of brain function. To treat neuropsychiatric disorders with a brain-machine interface, we first have to understand how these disorders affect the brain and its neural activity, and what constitutes a healthy, “normal” brain state to begin with.

“I’m fascinated with how the brain works,” Shanechi said, “and I’m extremely excited about how much we can do by using engineering principles to understand the brain and treat its disorders.”

Shanechi works closely with neurosurgeons, neurophysiologists and hardware designers to implement her algorithms and test them in patients, which is one of the many reasons she chose to come to USC Viterbi: the proximity to the Keck School of Medicine at USC and the emphasis on interdisciplinary research.

“USC provides a unique opportunity with the medical school close by. This enables a close collaboration with neurosurgeons and neurologists to build a brand new brain-machine interface program.”