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On Abstract Intelligence and Brain Informatics: Mapping Cognitive Functions of the Brain onto its Neural Structures

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  • Yingxu Wang

    (Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada)

Abstract

A key notion in abstract intelligence and cognitive informatics is that the brain and natural intelligence may only be explained by a hierarchical and reductive theory that maps the brain through the embodied neurological, physiological, cognitive, and logical levels from bottom-up induction and top-down deduction. This paper presents an abstract intelligence framework for modeling the structures and functions of the brain across these four levels. A set of abstract intelligent model, cognitive functional model, and neurophysiological model of the brain is systematically developed. On the basis of the abstract intelligent models of the brain at different levels, the conventionally highly overlapped, redundant, and even contradicted empirical observations in brain studies and cognitive psychology may be rigorously clarified and neatly explained. The improved understanding about the brain has led to the development of a wide range of novel technologies and systems such as cognitive computers, cognitive robots, and other applied cognitive systems.

Suggested Citation

  • Yingxu Wang, 2012. "On Abstract Intelligence and Brain Informatics: Mapping Cognitive Functions of the Brain onto its Neural Structures," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 6(4), pages 54-80, October.
    • Handle: RePEc:igg:jcini0:v:6:y:2012:i:4:p:54-80
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jcini.2012100103
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    Cited by:

    1. Yingxu Wang, 2013. "Cognitive Linguistic Perspectives On The Chinese Language," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 237-260.

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