A Systems Architecture Approach to the Brain: From Neurons to ConsciousnessAndrew Coward Tuesday 14th February 2006 at 11am
AbstractIt can be demonstrated on system theoretical grounds that any system which learns to perform many behavioural features with limited information handling resources is constrained within a set of bounds called the recommendation architecture by the requirement to find a compromise between the need to conserve physical information handling resources and the need to learn without severe interference with earlier learning. Overall architecture, the definition of modules and components, and even device algorithms are all constrained, with the severity of the constraints increasing as the ratio of features to resources increases. Algorithms widely used in artificial neural networks cannot be used in some major subsystems of the recommendation architecture. There are strong resemblances between the physical forms of a system within the recommendation architecture bounds and the physiology of the human brain including separations between and functions of the cortex, hippocampus, thalamus, basal ganglia, cerebellum, hypothalamus and amygdala; the internal organization of the cortex into layers, columns and areas; and the topology and synaptic algorithms of neurons. Detailed psychological observations of a wide range of cognitive phenomena, including semantic, episodic, working and procedural memory; processes such as arithmetic; the deficits resulting from physical damage; and sleep with dreaming can be modelled in a physiologically plausible manner by a system within the recommendation architecture bounds. Learning can be bootstrapped from experience with minimal and plausible a priori information. Many phenomena labelled "conscious" can be modelled in terms of physiology. Electronic systems within the recommendation architecture bounds confirm the capabilities of the architecture. For more information, see Andrew's book: A System Architecture Approach to the Brain: From Neurons to Consciousness. Short resumeL. Andrew Coward is a research fellow in the Department of Computer Science in the Faculty of Engineering and Information Technology at the Australian National University. As can be seen from Andrew's CV, he has wide experience in the design of operationally complex real time control systems. The architectural form of such systems is strongly constrained by the combination of operational complexity, limited information handling resources, and the need to modify features without excessive side effects on other features. Mr Coward's primary research objective is to understand the cognitive behaviour of the human brain in terms of neurophysiology, and to build electronic systems with similar behaviour. The starting point is that the combination of cognitive complexity, limited information handling resources and the need to learn without excessive interference with prior learning results in natural selection pressures constraining mammal brains into a specific architectural form called the recommendation architecture, although there is minimal resemblance between that form and the form for operationally complex electronic system architectures. The physical form and processes of a system with the recommendation architecture strongly resemble the physiological structures and processes of the human brain. Andrew's published work includes papers, book chapters and a book. |