The Cognitive Informatics Theory and Mathematical Models of Visual Information Processing in the Brain

It is recognized that the internal mechanisms for visual information processing are based on semantic inferences where visual information is represented and processed as visual semantic objects rather than direct images or episode pictures in the long-term memory. This article presents a cognitive informatics theory of visual information and knowledge processing in the brain. A set of cognitive principles of visual perception is reviewed particularly the classic gestalt principles, the cognitive informatics principles, and the hypercolumn theory. A visual frame theory is developed to explain the visual information processing mechanisms of human vision, where the size of a unit visual frame is tested and calibrated based on vision experiments. The framework of human visual information processing is established in order to elaborate mechanisms of visual information processing and the compatibility of internal representations between visual and abstract information and knowledge in the brain.

[1]  Yingxu Wang.  Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence (Advances in Cognitive Informatics and Natural Intelligence (Acini) Book Series) , 2009 .

[2]  Phil Turner,et al.  Exploration of Space, Technology, and Spatiality: Interdisciplinary Perspectives , 2008 .

[3]  H. Bastian.  Sensation and Perception.—I , 1869, Nature.

[4]  Yingxu Wang,et al.  The Theoretical Framework of Cognitive Informatics , 2007, Int. J. Cogn. Informatics Nat. Intell..

[5]  Yingxu Wang,et al.  On Cognitive Informatics , 2002, Proceedings First IEEE International Conference on Cognitive Informatics.

[6]  D. Hubel,et al.  Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.

[7]  Jr. Allen B. Tucker,et al.  The Computer Science and Engineering Handbook , 1997 .

[8]  G. Kanizsa,et al.  Organization in Vision: Essays on Gestalt Perception , 1979 .

[9]  Xudong Guan,et al.  Main retina information processing pathways modeling , 2010, IEEE ICCI.

[10]  Yingxu Wang,et al.  Software Engineering Foundations: A Software Science Perspective , 2007 .

[11]  Carla H. Lagorio,et al.  Psychology , 1929, Nature.

[12]  Yingxu Wang,et al.  On Abstract Intelligence: Toward a Unifying Theory of Natural, Artificial, Machinable, and Computational Intelligence , 2009, Int. J. Softw. Sci. Comput. Intell..

[13]  Yingxu Wang.  Inference Algebra (IA): A Denotational Mathematics for Cognitive Computing and Machine Reasoning (I) , 2011, Int. J. Cogn. Informatics Nat. Intell..

[14]  David S. Walker,et al.  A Theory of Organizational Cognition , 2009 .

[15]  MengChu Zhou,et al.  Short-Term Schedulability Analysis of Multiple Distiller Crude Oil Operations in Refinery With Oil Residency Time Constraint , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[16]  Yingxu Wang,et al.  A Computational Simulation of the Cognitive Process of Children Knowledge Acquisition and Memory Development , 2011, Int. J. Cogn. Informatics Nat. Intell..

[17]  Yingxu Wang,et al.  Contemporary Cybernetics and Its Facets of Cognitive Informatics and Computational Intelligence , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Lawrence K. Cormack,et al.  An Introduction to the Visual System: References , 1996 .

[19]  Yiyu Yao,et al.  In Search of Effective Granulization with DTRS for Ternary Classification , 2011, Int. J. Cogn. Informatics Nat. Intell..

[20]  Andrew Targowski.  Cognitive Informatics and Wisdom Development: Interdisciplinary Approaches , 2010 .

[21]  Luca Cardelli,et al.  The Computer Science and Engineering Handbook , 1997 .

[22]  Gustavo Abib,et al.  Organizational and technological implications of cognitive machines: designing future information management systems , 2011 .

[23]  D H Hubel,et al.  Brain mechanisms of vision. , 1979, Scientific American.

[24]  Yingxu Wang,et al.  Deductive Semantics of RTPA , 2008, Int. J. Cogn. Informatics Nat. Intell..

[25]  Yingxu Wang,et al.  On System Algebra: A Denotational Mathematical Structure for Abstract System Modeling , 2008, Int. J. Cogn. Informatics Nat. Intell..

[26]  A. Grafstein.  MIT Encyclopedia of the Cognitive Sciences , 2000 .

[27]  Yingxu Wang,et al.  Cognitive informatics models of the brain , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[28]  Andrew Targowski.  The Cognitive Informatics Approach towards Wisdom , 2010 .

[29]  Stephen K. Reed,et al.  Pattern recognition and categorization , 1972 .

[30]  Yingxu Wang,et al.  On Contemporary Denotational Mathematics for Computational Intelligence , 2008, Trans. Comput. Sci..

[31]  M Glickstein,et al.  The discovery of the visual cortex. , 1988, Scientific American.

[32]  Yingxu Wang,et al.  On Visual Semantic Algebra (VSA): A Denotational Mathematical Structure for Modeling and Manipulating Visual Objects and Patterns , 2009, Int. J. Softw. Sci. Comput. Intell..

[33]  Stephen K. Reed,et al.  The role of analogy in transfer between similar problem states , 1974 .