About the book
The mind is what the brain does. This book maps a mind model to the corresponding brain so as to deepen our understanding of both the brain and the mind by unveiling computational mechanisms. That is why the words “Brain-Mind” are hyphenated in the title. The book attempts to unify natural intelligence with artificial intelligence, through “hardening” of “soft” sciences and the holism of “hard” sciences. It approaches intelligence in terms of not only what intelligence is but also how intelligence arises through lifetime.
This volume strives to unify natural intelligence with artificial intelligence.
This book has published the first developmental model of the brain-mind. The term “development” means that the book explains not only how the brain-mind works, but also how the brain-mind emerges — a deeper causality. The author argued that one cannot understand how the brain-mind works without first understanding how the brain-mind emerges. This seems to be the first computational model about how the brain-mind emerges. Because the book explained how the brain-mind emerges, it is also the first that explained computationally how the brain-mind works.
Other related books are either qualitative but not computational (e.g., How the Mind Works, by Steven Pinker), or computational but less complete (i.e., about mainly sensory processing, e.g., Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, by Peter Dayan and Laurence F. Abbott).
Examples of disciplinary questions related to the material in this book:
- Biology: How does each autonomous cell interact with the environment to give rise to animal behaviors, and what cellular roles is the genome likely to play?
- Neuroscience: From an overarching perspective, how does a brain self-wire, perform top-down attention, and develop its functions?
- Psychology: How does an integrated brain architecture accomplish multiple psychological learning models and develop brain’s external behaviors?
- Computer Science: How does a machine auto-program for general purposes and how do emergent universal Turing machines explain brain intelligence and AI?
- Electrical Engineering: How does a brain-like network perform general-purpose, nonlinear, feedback sensing-and-control, beyond traditional nonlinear control?
- Mathematics: How does a brain-like network perform general-purpose, nonlinear optimization, and how does a brain realize emergent functionals?
- Physics: How do meanings arise from physics, and how does a brain-like network treat space and time in a unified way, reminiscent of relativity?
- Social sciences: How do computational principles of human brains provide insight into possible solutions to a variety of social and political problems?
Since there seemed to be no other reviewers who had all the required disciplinary knowledge (biology, neuroscience, psychology, computer science, electrical engineering, and mathematics) that is necessary to understand the book material, the BMI Press, the publisher of the Brain-Mind Institute, published the book. |
Short bio about the author
Juyang Weng received his BS degree from Fudan University, and MS and PhD degrees from University of Illinois, Urbana-Champaign, all in Computer Science. He is a professor at the Dept. of Computer Science and Engineering, a faculty member of the Cognitive Science Program and the Neuroscience Program, Michigan State University, East Lansing, Michigan, USA. He is a fellow of IEEE. |
