February 14, 2022

Join Zoom Meeting: https://us02web.zoom.us/j/87353143297?pwd=SjJlMEt4WnRIQ0tZZU1jRkJSR3luZz09
Meeting ID: 873 5314 3297
Passcode: 658734

Behavior and cognition are driven by the coordinated activity of populations of neurons in the brain. A major challenge in systems neuroscience is to infer the computational principles underlying the activity of the neural populations. What are the algorithms implemented by these neural populations? How can we design experiments and analyses with hypotheses about computation in mind? My research group will develop the theory, modeling, and machine learning techniques needed to realize this vision of “reverse engineering†computation in the brain. Progress in this research could lead to new insights into treating neurological injuries and disorders, new paradigms for optimizing our behavior and cognition, and new approaches to generating artificial intelligence.

In this talk, I will present lines of previous, ongoing, and proposed research that highlight the potential of this vision. First, I will present a line of brain-computer interface experiments and modeling that revealed principles guiding neural populations as they reorganize during learning. Here, dimensionality reduction and convex optimization provided insight into the constraints faced by neural populations. Second, I will present a framework of network modeling for identifying the computations performed by a population of recorded neurons. Here, we trained sequential variational autoencoders to learn nonlinear dynamical systems (NLDS) capable of generating observed single-trial neural population activity. We then developed techniques for identifying the computations performed through the dynamics of the NLDS. Finally, I will propose future directions for leveraging these tools and identified principles of neural computation toward i) accelerating the brain’s ability to learn, ii) optimizing optogenetic control of neural population dynamics, and iii) understanding the interplay between attention and decision making in the brain.

This lecture will be streamed live on the Allen School YouTube Channel. See https://www.cs.washington.edu/events/colloq_info for more information