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Dr. Yanliang Shi ECE Faculty Candidate Seminar

Event Type
Electrical and Computer Engineering
B02 CSL Auditorum & Zoom
Feb 20, 2024   10:00 - 11:00 am  
Dr. Yanliang Shi, Associate Research Scholar, Princeton University
Angie Ellis
Originating Calendar
Illinois ECE Calendar

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.

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