Juyang Weng

Computer Science, Cognitive Science, and Neuroscience

Fudan University
Shanghai, China
and
Michigan State University
East Lansing, Michigan U.S.A
weng@cse.msu.edu

Abstract

On one hand neuroscience is rich in data and poor in theory.   On the other hand, many computer scientists are busy with engineering inspired methods, not motivated by brain inspired methods.  However, in this talk, I argue that it is no longer true that “we do not know how the brain works”.   The knowledge of computer science is also necessary to understand how the brain works.   Supported by a series of experimental studies known as Where What Networks (WWN-1 through WWN-8), I present an overarching but intuitive analogical model called bridge-islands.   Each island is either a sensor (e.g., an eye or an ear) or an effector (an arm, or a gland).   The brain is a multi-exchange bridge that connects to all the islands in bidirectionally.   It is not productive to model the brain statically as a connected set of Brodmann areas, because in the born blind, the visual areas are automatically assigned to audition and touch.  Therefore, the bridge-island model describes how various brain areas emerge from pre-natal and post-natal activities based on largely statistics.  In other words, the brain wires itself.   We also discuss how the self-wired basic circuits become motivated through four additional neural transmitters beyond glutamate and GABA --- serotonin, dopamine, acetylcholine, and norepinephrine.  

Short Bio

Juyang (John) Weng is a professor at the Dept. of Computer Science and Engineering, the Cognitive Science Program, and the Neuroscience Program, Michigan State University, East Lansing, Michigan, USA, and a Changjiang visiting professor a Fudan University, Shanghai, China.  He received his BS degree from Fudan University in 1982, his MS and PhD degrees from University of Illinois at Urbana-Champaign, 1985 and 1989, respectively, all in Computer Science.  From August 2006 to May 2007, he was also a visiting professor at the Department of Brain and Cognitive Science of MIT.   His research interests include computational biology, computational neuroscience, computational developmental psychology, biologically inspired systems, computer vision, audition, touch, behaviors, and intelligent robots.  He is the author or coauthor of over two hundred fifty research articles, including a book Natural and Artificial Intelligence: Introduction to Computational Brain-Mind. He is an editor-in-chief of International Journal of Humanoid Robotics and an associate editor of the IEEE Trans. on Autonomous Mental Development, and the editor-in-chief of the Brain-Mind Magazine. He is instrumental in the establishment and operation of the Brain-Mind Institute, a nonprofit for cross-disciplinary education and research.  He was an associate editor of IEEE Trans. on Pattern Recognition and Machine Intelligence, an associate editor of IEEE Trans. on Image Processing.  He is a Fellow of IEEE.