Adam Willats
BME PhD Thesis Proposal Presentation

Date: Thursday, March 19th 2020
Time: 10am – noon
Location: Coda, room 1115 Druid Hills

Committee Members:
Christopher Rozell (Advisor)
Robert Butera

Mark Davenport

Chethan Pandarinath

Garrett Stanley

Title: Development and characterization of closed-loop control to understand neural circuits
Abstract:
For decades, engineers have used feedback control to actuate a system based on measured activity to reduce variability, compensate for imperfect measurements, drive systems to desired set points, and decouple connected systems. A growing community is developing and applying closed-loop stimulation strategies at the cellular and circuit level to understand the brain and treat disorders. The advent of optogenetic stimulation has accelerated the potential for effective closed-loop stimulation by facilitating actuation strategies that can be more precisely targeted and have minimal recording artifacts compared to conventional microelectrode stimulation. 

        While many such new actuation and measurement tools have recently become available for neural systems, we require principled algorithmic tools for designing feedback controllers to use these neural interfaces. A gap still exists in making these tools modular, comprehensive, and straightforward to develop from prototype to final implementation. Alongside algorithmic advances, the neuroengineering community must also deepen its scientific understanding of how best to leverage these tools to more precisely answer questions of function in neural circuits. In this work my goals are to extend the framework for designing and implementing closed-loop control approaches, and to characterize how and why this framework can be used to identify tightly coupled neural circuits more effectively.