© 2019

Yuqing Zhu

Theory + Practice

a beginning

I am a PhD student in the lab of Jason MacLean

at the University of Chicago, and part of the computational neuroscience program.

My first fascination is with the visual system (the most elegant and coy sensory system), and the first tool in my kit is mathematical modeling. I also have a healthy interest in the collusion between neuroscience and artificial intelligence.

Publications:

Bojanek K*, Zhu Y*, MacLean J. 2019. Cyclic transitions between higher order motifs underlie sustained activity in asynchronous sparse recurrent networks.

*co-first-authors.

Preprint available on biorXiv.

In this study we ask how an extremely sensitive and complex system, such as a biological brain, maintains stable activity across time. We algorithmically build spiking neural network models (SNNs) with neocortical dynamics. Using a combination of graph theory, information theory, and probabilistic tools, we explore the mechanisms of sustained activity in network simulations. The focus of our analysis is on beyond-pairwise interactions, especially triangle motifs, that manifest in the network through time.

I am currently asking:

How do networks of neurons - both biological and mathematical - change during learning?

Previously:

In my first year in the PhD program at UChicago, I rotated through four labs, dabbling in machine learning, connectomics, and training rhesus macaque monkeys and mice. 

 

Prior to enrolling at UChicago, I have been a research assistant in the labs of:

 

I. Josef Parvizi at Stanford Medicine,
where I studied human visual perception of symbols using electrocorticography

II. Marina Bedny at Johns Hopkins University,

where I studied the development of human mathematical cognition
 

III. Chung-Chuan Lo at National Tsing Hua University, where I used a Drosophila full-brain simulation to survey the effects of synaptic long-term potentiation (LTP) on signal propagation and visual learning.

 

IV. Rong Xue at the Chinese Academy of Sciences, where I probed the limits of diffusion tensor imaging (DTI) in tracing human sensory pathways.

I completed my B.S. in neuroscience and cognitive science at Johns Hopkins University in Dec 2016. My focal areas were sensory systems, 

computational models of cognition, and philosophy of mind.