Modularization for brain and brain-inspired neural networks

Abstract

Brain is the most complex part of our body. It is not only the actional control center but also the source of intelligence and consciousness. To support the complex biochemical dynamics and information processing, the brain network exhibits modular organization in multiple scales and modalities. While such modularization patterns may be defined by clustering techniques, it is still unclear what principles underlie their development and how modularization computationally improves neuronal encoding and network performance. In this presentation, we will discuss our methodological thinking about the modular structure and dynamic reconfiguration of the brain from both the dynamical system and computational intelligence perspectives.

About the speaker

Shi Gu 顾实

Dr. Gu is currently a professor of computer science and engineering at the University of Electronic Science and Technology of China. He obtained his Ph.D. from the University of Pennsylvania (2011-2016) under the supervision of Dr. Dani S. Bassett, with his doctoral thesis titled “Control Theoretic Analysis on Brain Networks.” He has long been working in the interdisciplinary fields of neuroscience and machine learning. Dr. Gu received the One Thousand Young Talent Program Grant and was recognized by Forbes China as one of the "30 Under 30" in 2017. His current research interests include developing network methods to analyze brain dynamics, modeling neurodevelopment using data-driven approaches, and creating algorithms for brain-inspired learning.