Distinguished Lecture Series : Visualizing the multi-scale complexity of the brain


Professor Guo-Qiang Bi

School of Life Sciences
University of Science and Technology of China (USTC)
Center for Brain Information
Shenzhen Institute of Advanced Technology

Professor Guo-Qiang Bi received his B.S. in physics from Peking University and Ph.D. in biophysics from UC Berkeley. After postdoctoral research at UCSD, he joined the Department of Neurobiology of the University of Pittsburgh as an Assistant Professor and promoted to Associate Professor with tenure. In 2007, He established the Laboratory of Neurophysics at USTC, where he has been Xinchuang Professor and Changjiang Scholar, and chair of the Department of Neurobiology and Biophysics. Since 2020, he has been co-appointed as professor and funding director of the Interdisciplinary Center for Brain Information, Shenzhen Institute of Advanced Technology. His main research interest is mechanisms and principle of synaptic plasticity and of learning. In recent years, he and colleagues have been developing and applying new tools of optical imaging and electron microscopy to dissect the multi-scale structure of neuronal synapses and brain circuits.

Date: 15 June 2021

Time: 10:00 – 11:30 a.m.

Venue: Online via Zoom ( Meeting ID: 981 8581 9842)

Relevant documents: PowerPoint Slides


The brain is complex over multiple length-scales, from many protein molecules forming intricate nano-machines in a synapse to many neurons forming interconnected networks across the brain. Unraveling this multi-scale complexity is fundamental to our understanding of brain function and disease. In this lecture, I will introduce advances in visualizing the complex, multi-scale structures in the brain. Emphasis will be on new imaging techniques, including cryo electron tomography and correlative light-electron microscopy that enabled revealing in situ organization of synaptic molecules, and ultra-high speed volumetric imaging method VISoR developed to map brain-wide circuits at subcellular resolution. I will also discuss challenges and opportunities for interdisciplinary research collaboration to analyze and understand the enormous data generated by these cutting-edge technologies.

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