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How Brain-Mind Works with Vision but Beyond:
Introduction to a Whole-Brain Theory

Juyang WENG

Computer Science, Cognitive Science and Neuroscience
Fudan University, Shanghai, China and
Michigan State University, East Lansing, MI 48824 USA

weng@cse.msu.edu

Abstract

Neuroscience has made impressive advances, but there is a lack of a computational whole-brain theory. I would like to present a simplified computational theory in an intuitive language about how the brain wires itself as a multi-interchange bridge that bi-directionally connects many islands where each island is a sensor or effector. The wiring process of the brain is highly self-supervised while the baby manipulates an object, e.g., sucking a milk bottle. My theory explains that the way a human brain works with vision and visual behaviors is similar to its ways to work with other sensory modalities, other sensory-modality-dependent behaviors, and integrative capabilities such as languages, emotion, and consciousness. I explain how the self-wired basic circuits that use glutamate and GABA become motivated through four additional neural transmitters beyond glutamate and GABA --- serotonin, dopamine, acetylcholine, and norepinephrine. A layman or a researcher in another discipline can get a gist of this theory by attending this short introductory talk. However, to be fully convinced and to effectively use the theory, he must attend some brain-integrated courses in biology, neuroscience, cognitive science, computer science, electrical engineering, and mathematics. I argue that only the Brain-Mind Institute (BMI) currently offer such a series of brain-integrated courses because the material of each BMI course is guided by the whole-brain theory, through the course instructors and course discussions.

Short Bio

Juyang (John) Weng is a professor at the Department of Computer Science and Engineering, the Cognitive Science Program, and the Neuroscience Program, Michigan State University, East Lansing, Michigan, USA. 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 a Fellow of IEEE, an editor-in-chief of International Journal of Humanoid Robotics and an associate editor of the new IEEE Transactions on Autonomous Mental Development. He has chaired and co-chaired some conferences, including the NSF/DARPA funded Workshop on Development and Learning 2000 (1st ICDL), 2nd , 7th, and 8th ICDL. He was the Chairman of the Governing Board of the International Conferences on Development and Learning (ICDLs) (2005-2007), http://cogsci.ucsd.edu/~triesch/icdl/), chairman of the Autonomous Mental Development Technical Committee of the IEEE Computational Intelligence Society (2004-2005), an associate editor of IEEE Trans. on Pattern Recognition and Machine Intelligence, and IEEE Trans. on Image Processing.



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Last updated: December 18, 2013