| Title | Mathematical Models of the Mind, Cognitive Algorithms, and Engineering Applications — Language and Cognition: Concepts, Emotions, and Music |
| Speaker | Dr. Leonid Perlovsky |
| Chair | Sundaram Suresh |
Abstract
Why human brain uses different neural circuits for language comprehension and cognitive understanding? How language is related to cognition? Do we think with language, or do we use language just to express already formulated thoughts? Why children can talk about virtually everything by the age of 5 or 7, but cannot act like adults? How do we know which words corresponds to which object? And why animals do not have human-type language? Why human language and human cognition go together, and no animal has only one of these? Language and cognition are so intertwined that it is difficult to imagine what human cognition is without language.
The talk discusses a mathematical model of interacting language and cognition. It describes two parallel hierarchies of language and cognition from objects to abstract ideas. Language is learned from surrounding language early in life, and then throughout life it guides learning of cognition. This model is suitable for an engineering development of self-learning of language and cognition. Existing data indicates that this model corresponds to the mechanisms of the brain-mind. This model suggests an explanation for a well known but not well explained “illusion of understanding”: abstract ideas often are discussed using words without understanding cognitive concepts; language brain areas are active but cognitive are not. This model addresses fundamental semiotic questions about what are signs and symbols, how signs acquire meanings, and what it is.
Cognitive concepts-representations are acquired from experience under “supervision” of language. This interaction requires a special drive and emotions. These emotions are different from basic emotions (rage, hanger, sadness). We discuss mechanisms of these drive and emotions, and relate them to musical emotions. This touches on another 2500 years old mystery: what is the cognitive function of music and why it emerged in evolution. Recent experimental results are presented.
We briefly touch on relating this model to hot issues in psychology: cognitive dissonance, mirror neurons, higher human abilities, the cognitive functions of beautiful, music, sublime in the mind, cognition, and evolution. Studying this set of ideas in simulation and experiments is a large program. We discuss our group progress and a number of directions for future research. Dozens of master and PhD dissertations wait to be written.
Biography
Dr. Leonid Perlovsky is Visiting Scholar at Harvard University, Principal Research Physicist and Technical Advisor at the Air Force Research Laboratory. He leads research on cognitive algorithms for detection, tracking fusion, mathematical models of the mind, language and cognition, evolution of cultures. As Chief Scientist at Nichols Research, a $500mm high-tech organization, he led the corporate research in intelligent systems. He served as professor at Novosibirsk University and New York University; as a principal in commercial startups developing tools for biotechnology, text understanding, and financial predictions. He is invited as a keynote plenary speaker and tutorial lecturer worldwide; published more than 450 papers; 12 book chapters; and 4 books including “Neural Networks and Intellect,” Oxford University Press, 2001 (currently in the 3rd printing) and “Emotional, Cognitive, Neural Algorithms with Engineering Applications,” Springer 2011; awarded 2 patents. Dr. Perlovsky is active at the IEEE and the International Neural Network Society (INNS); he serves on the INNS Board of Governors, as a Chair of The Award Committee. He serves on the Editorial Board of twelve professional journals, including Editor-in-Chief for “Physics of Life Reviews” (IF=7.2, T-F rank#4 in the world). He received National and International awards including the Best Paper Award 2001 from Zvezda, a leading Russian essayistic magazine; the Gabor Award 2007, the top engineering award from the INNS; and the John McLucas Award 2007, the highest US Air Force Award for basic research.
