We are interested in understanding the relationship between structure, function, and metabolism in neural networks. Especially, what is the underlying principle for shaping the diagrams of neural networks? How is the information processed and function implemented based on the brain structure? To address these questions, we primarily use the connectome from brain neuroimaging data, the anatomical datasets, apply statistical physics, nonlinear dynamics, and cognitive neuroscience methods, as well as develop a series of novel computational models. Our research builds a bridge across different levels of complex neural systems, such as neuronal, column level, regional, and cortical levels. Our most recent projects focus on exploring the mechanism of information processing and function implemented in the young adult primate brains as well as the human brain during development.

We particularly welcome students with backgrounds in physics, mathematics, computer science, electronic engineering, or psychology to join our team.