A System Architecture Approach To The Brain
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A System Architecture Approach to the Brain
This book is the integrated presentation of a large body of work on understanding the operation of biological brains as systems. The work has been carried out by the author over the last 22 years, and leads to a claim that it is relatively straightforward to understand how human cognition results from and is supported by physiological processes in the brain. This claim has roots in the technology for designing and manufacturing electronic systems which manage extremely complex telecommunications networks with high reliability, in real time and with no human intervention. Such systems perform very large numbers of interacting control features. Although there is little direct resemblance between such systems and biological brains, the ways in which these practical considerations force system architectures within some specific bounds leads to an understanding of how different but analogous practical considerations constrain the architectures of brains within different bounds called the Recommendation Architecture. These architectural bounds make it possible to relate cognitive phenomena to physiological processes.
Towards a Theoretical Neuroscience: from Cell Chemistry to Cognition
Author: L Andrew Coward
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-08-23
The book explains how to understand cognition in terms of brain anatomy, physiology and chemistry, using an approach adapted from techniques for understanding complex electronic systems. These techniques create hierarchies of information process based descriptions on different levels of detail, where higher levels contain less information and can therefore describe complete cognitive phenomena, but are more approximate. The nature of the approximations are well understood, and more approximate higher level descriptions can therefore be mapped to more precise detailed descriptions of any part of a phenomenon as required. Cognitive phenomena, the anatomy and connectivity of major brain structures, neuron physiology, and cellular chemistry are reviewed. Various cognitive tasks are described in terms of information processes performed by different major anatomical structures. These higher level descriptions are selectively mapped to more detailed physiological and chemical levels.
Perception-Action Cycle
Author: Vassilis Cutsuridis
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-02-02
The perception-action cycle is the circular flow of information that takes place between the organism and its environment in the course of a sensory-guided sequence of behaviour towards a goal. Each action causes changes in the environment that are analyzed bottom-up through the perceptual hierarchy and lead to the processing of further action, top-down through the executive hierarchy, toward motor effectors. These actions cause new changes that are analyzed and lead to new action, and so the cycle continues. The Perception-action cycle: Models, architectures and hardware book provides focused and easily accessible reviews of various aspects of the perception-action cycle. It is an unparalleled resource of information that will be an invaluable companion to anyone in constructing and developing models, algorithms and hardware implementations of autonomous machines empowered with cognitive capabilities. The book is divided into three main parts. In the first part, leading computational neuroscientists present brain-inspired models of perception, attention, cognitive control, decision making, conflict resolution and monitoring, knowledge representation and reasoning, learning and memory, planning and action, and consciousness grounded on experimental data. In the second part, architectures, algorithms, and systems with cognitive capabilities and minimal guidance from the brain, are discussed. These architectures, algorithms, and systems are inspired from the areas of cognitive science, computer vision, robotics, information theory, machine learning, computer agents and artificial intelligence. In the third part, the analysis, design and implementation of hardware systems with robust cognitive abilities from the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning are discussed.