ECE Faculty Candidate Seminar
Dr. Yanliang Shi
Associate Research Scholar, Princeton University
Tuesday, February 20, 2024, 10:00-11:00 am
B02 CSL Auditorium or via Zoom
Title: A multiscale theoretical framework for the neural dynamics and computation
Abstract: Recent advances in massively parallel neural recording technologies enabled monitoring activity of neural population across multiple brain regions during complex behavior, mapping whole-brain wiring diagrams and gene-expression profiles. These large-scale neural datasets open the opportunity to investigate neural circuits, systems, and even brain functionality in its entirety. In this talk, I will present a multi-scale theoretical framework for the neural dynamics and computation.
I will show the dynamical system approaches enable us to causally predict functional neural dynamics based on biological structure across multiple scales, ranging from local cortical circuits to cortex-wide dynamics to brain-wide dynamics. First, I will discuss a dynamical network model of cortical columns that explains observed spatiotemporal cortical dynamics of primate visual cortex during spatial attention. Second, I will present the dynamical system model of mesoscopic dynamics across the mouse cortex which integrates datasets of inter-regional anatomical connectivity and widefield calcium imaging of neural activity across the mouse dorsal cortex. Third, I will discuss brain-wide neural activity during complex behavior by analyzing large-scale neuropixel recordings of spiking activity. Specifically, I will show how to utilize biological structural features such as spatial gene-expression profiles to create an atlas of neural electrophysiological features across the entire mouse brain.
Last, as my research plan, I will discuss how to map neural dynamics to algorithmic representation of neural computation, build a complete framework that links biological structure to neural dynamics to neural computation, and apply this framework to multi-scale neural systems.
Yanliang Shi is an Associate Research Scholar at Princeton University in Prof. Tatiana Engel’s group and a researcher in the International Brain Laboratory. He applies theoretical and computational approaches to analyze large-scale neuroscience datasets of electrophysiology, calcium imaging, genetics and connectome, with the aim of understanding mechanisms of brain dynamics and computation. Before joining Princeton in 2023, he was a postdoctoral fellow at Cold Spring Harbor Laboratory from 2018 to 2022. He received Ph.D. in Physics from Stony Brook University in 2018. Yanliang was a Swartz Foundation Fellow in Theoretical Neuroscience from 2019 to 2021.
