“Computational Neuroengineering: Building the Algorithmic Foundations for Interacting with Neural Systems Across Multiple Scales”

This seminar is hosted by the Department of Electrical & Systems Engineering.

Abstract Neuroengineering research has rapidly advanced technologies to interface with neural systems at multiple scales. These advances are leading to an increasing desire to build closed-loop systems that exploit interaction between biology and technology to maximize the effectiveness of both scientific discovery and clinical therapies. In contrast to traditional computational neuroscience research that focuses on post-experiment analysis, achieving this goal requires the parallel emergence of a discipline of “computational neuroengineering” to build complementary algorithmic technology that can operate in real-time with limited data. In this talk I will describe our recent work drawing on diverse data science disciplines (including machine learning, signal processing, control theory, optimization, and information theory) to build online algorithms for use in a variety of closed-loop interactions with neural systems. I will demonstrate the effectiveness of these approaches at enabling in a wide variety of new applications spanning multiple scales, including automated high-throughput patch clamp electrophysiology of neurons in brain slices, closed-loop optogenetic stimulation of neural circuits, and novel non-invasive brain-machine interfaces for controlling complex systems.

For inquiries contact Francesca Allhoff.