From Multi-Omic Data to Brain Diseases, Digital Twin Brains, and Brain-Inspired AI

15:05 – 15:55: Keynote Speech - Professor Jianfeng Feng

From Multi-Omic Data to Brain Diseases, Digital Twin Brains, and Brain-Inspired AI 

Synopsis

AI and proteomics are recently believed as facing a revolutionary phase and could fundamentally change our understanding of diseases (brain disorders). Using one of the typical mental disorders and AD as examples, we explore the etiology of the disease with genomic, proteomic and other type of omic data and novel AI algorithms. The discoveries subsequently enable us to subtype various diseases and then develop different treatment strategies in TMS and drug therapy. Some further developments aiming to integrate micro-, meso- and macroscopic data results are discussed. Furthermore, equipped with the knowledge we have about the brain, we developed a model of the whole human brain at the neuronal level (digital twin brain, DTB): 86B neurons and 100T synapses(parameters). Examples on applying DTB to medical applications are included. Finally, we developed a mathematical approach termed moment neuronal network to tackle many issues raised in DTB.