Glia-augmented artificial neural networks: foundations and applications

Sajedinia, Zahra (2015) Glia-augmented artificial neural networks: foundations and applications. Masters thesis, Memorial University of Newfoundland.

[img] [English] PDF - Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

Download (1MB)


Information processing in the human brain has always been considered as a source of inspiration in Artificial Intelligence; in particular, it has led researchers to develop different tools such as artificial neural networks. Recent findings in Neurophysiology provide evidence that not only neurons but also isolated and networks of astrocytes are responsible for processing information in the human brain. Artificial neural net- works (ANNs) model neuron-neuron communications. Artificial neuron-glia networks (ANGN), in addition to neuron-neuron communications, model neuron-astrocyte con- nections. In continuation of the research on ANGNs, first we propose, and evaluate a model of adaptive neuro fuzzy inference systems augmented with artificial astrocytes. Then, we propose a model of ANGNs that captures the communications of astrocytes in the brain; in this model, a network of artificial astrocytes are implemented on top of a typical neural network. The results of the implementation of both networks show that on certain combinations of parameter values specifying astrocytes and their con- nections, the new networks outperform typical neural networks. This research opens a range of possibilities for future work on designing more powerful architectures of artificial neural networks that are based on more realistic models of the human brain.

Item Type: Thesis (Masters)
Item ID: 12146
Additional Information: Includes bibliographical references (pages 58-67).
Keywords: Artificial Neural Networks, Artificial Neuron-Glia Networks, Artificial Astrocyte Networks, Adaptive Neuro-Glia Fuzzy Inference Systems, Adaptive Neuro-Fuzzy Inference Systems
Department(s): Science, Faculty of > Computer Science
Date: May 2015
Date Type: Submission
Library of Congress Subject Heading: Neural networks (Computer science); Astrocytes--Computer simulation; Fuzzy systems

Actions (login required)

View Item View Item


Downloads per month over the past year

View more statistics