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The evolutionary emergence of neural organisation in computational models of primitive organisms

Jones, Benjamin Henry Demidecki (2010)
Ph.D. thesis, University of Birmingham.

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Abstract

Over the decades, the question why did neural organisation emerge in the way that it did? has proved to be massively elusive. Whilst much of the literature paints a picture of common ancestry the idea that a species at the root of the tree of nervous system evolution spawned numerous descendants the actual evolutionary forces responsible for such changes, major transitions or otherwise, have been less clear. The view presented in this thesis is that via interactions with the environment, neural organisation has emerged in concert with the constraints enforced by body plan morphology and a need to process information eciently and robustly. Whilst these factors are two smaller parts of a much greater whole, their impact during the evolutionary process cannot be ignored, for they are fundamentally signicant. Thus computer simulations have been developed to provide insight into how neural organisation of an articial agent should emerge given the constraints of its body morphology, its symmetry, feedback from the environment, and a loss of energy. The first major finding is that much of the computational process of the nervous system can be ooaded to the body morphology, which has a commensurate bearing on neural architecture, neural dynamics and motor symmetry. The second major finding is that sensory feedback strengthens the dynamic coupling between the neural system and the body plan morphology, resulting in minimal neural circuitry yet more ecient agent behaviour. The third major finding is that under the constraint of energy loss, neural circuitry again emerges to be minimalistic. Throughout, an emphasis is placed on the coupling between the nervous system and body plan morphology which are known in the literature to be tightly integrated; accordingly, both are considered on equal footings.

Type of Work:Ph.D. thesis.
Supervisor(s):Yao, Xin (1962-) and Senhoff, Bernard and Jin, Yaocho
School/Faculty:Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department:School of Computer Science
Subjects:Q Science (General)
Institution:University of Birmingham
ID Code:649
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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