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Reverse Engineering the Brain

Published

Author(s)

James S. Albus

Abstract

Reverse engineering the brain will require a deep understanding of how information is represented and how computation is performed in the brain. What are the functional operations? What are the knowledge data structures? How are messages encoded? How are relationships established and broken? How are images processed? How does the brain transform signals into symbols? How does the brain generate the incredibly complex colorful, dynamic internal representation that we all perceive to be external reality? The model presented here hypothesizes that each cortical hypercolumn together with its underlying thalamic nuclei performs as a Fundamental Computational Unit (FCU) consisting of a frame-like data structure (containing attributes and pointers) plus the computational processes and mechanisms required to build and maintain it. In behavior-generating areas of the brain, FCUs make decisions, set goals and priorities, generate plans, and control behavior. Pointers are used to define rules, grammars, procedures, plans, and behaviors. In sensory-processing areas of the brain, FCUs enable segmentation, grouping, and classification. Pointers stored in FCU frames link pixels and signals to objects and events in situations and episodes that are overlaid with meaning and emotional values. It is suggested that it may be possible to reverse engineer the human brain at the FCU level of fidelity using next-generation massively parallel computer hardware and software.
Proceedings Title
Proceedings of the Fall Symposium of the American Association for Artificial Intelligence (AAAI)
Conference Dates
November 7-9, 2008
Conference Location
Arlington, VA

Keywords

brain modeling, biologically inspired architectures, cognitive modeling, reverse engineering, cortical modeling

Citation

Albus, J. (2007), Reverse Engineering the Brain, Proceedings of the Fall Symposium of the American Association for Artificial Intelligence (AAAI), Arlington, VA (Accessed May 2, 2024)
Created November 9, 2007, Updated February 17, 2017