Events Calendar

AI SEMINAR

Speaker: Maryam Shanechi, Assistant Professor and Viterbi Early Career Chair

Talk Title: Closed Loop Brain Machine Interface Architecures

Abstract: A brain-machine-interface (BMI) is a system that interacts with the brain either to allow the brain to control an external device or to control the brain's state. While these two BMI types are for different applications, they can both be viewed as closed-loop control systems. In this talk I present our work on developing both these types of BMIs, specifically motor BMIs for restoring movement in paralyzed patients, a BMI for control of the brain state under anesthesia, and finally a new BMI for control of the brains neuropsychiatric state. Motor BMIs have largely used standard signal processing techniques. However, devising novel algorithmic solutions that are tailored to the neural system can significantly improve the performance of these BMIs. Here, I develop a novel BMI paradigm for restoration of motor function that incorporates an optimal feedback-control model of the brain and directly processes the spiking activity using point process modeling. I show that this paradigm significantly outperforms the state-of-the-art in closed-loop primate experiments. In addition to motor BMIs, I construct a new BMI that controls the state of the brain under anesthesia. This is done by designing stochastic controllers that infer the brain's anesthetic state from non-invasive observations of neural activity and control the real-time rate of drug administration to achieve a target brain state. I show the reliable performance of this BMI in rodent experiments. Finally, I show some of our recent results on the development of a BMI for closed-loop electrical stimulation to treat neuropsychiatric disorders in human patients.

Biography: Maryam Shanechi is an assistant professor and the Viterbi Early Career Chair in the Ming Hsieh Department of Electrical Engineering at the University of Southern California (USC). Prior to joining USC, she was an assistant professor in the School of Electrical and Computer Engineering at Cornell University. She received the B.A.Sc. degree in Engineering Science from the University of Toronto in 2004 and the S.M. and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 2006 and 2011, respectively. She is the recipient of the NSF CAREER Award and has been named by the MIT Technology Review as one of the worlds top 35 innovators under the age of 35 (TR35) for her work on brain-machine interfaces.


Host: Ashish Vaswani

Webcast: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=1bcb9ec6f2d24ea58d7a2237816965c01d

Location: Information Science Institute (ISI) - 1135

WebCast Link: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=1bcb9ec6f2d24ea58d7a2237816965c01d

Audiences: Everyone Is Invited

Contact: Alma Nava / Information Sciences Institute