Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children

The purpose of this research was to explore, analyse and describe the brainwave pattern of Autism Spectrum Disorder (ASD) children using Quantitative Electroencephalogram (qEEG) and suggesting the right neurofeedback training (NFT) protocol. Quantitative Electroencephalogram primarily measures th...

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Main Author:	Nurul Aina, bt Mohd Mahayuddin
Format:	Thesis
Language:	English English
Published:	2015
Subjects:	Q Science (General)
Online Access:	http://ir.unimas.my/id/eprint/10760/1/Electroencephalogram%20%28EEG%29%20Signature%20of%20Autism%20Spectrum%20Disorder%20%28ASD%29%20Children%20%2824pgs%29.pdf http://ir.unimas.my/id/eprint/10760/8/Nurul%20Aina%20Mohd%20Mahayuddin%20ft.pdf
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spelling	my-unimas-ir.107602023-05-23T07:57:36Z Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children 2015 Nurul Aina, bt Mohd Mahayuddin Q Science (General) The purpose of this research was to explore, analyse and describe the brainwave pattern of Autism Spectrum Disorder (ASD) children using Quantitative Electroencephalogram (qEEG) and suggesting the right neurofeedback training (NFT) protocol. Quantitative Electroencephalogram primarily measures the electric potential field at the scalp surface. Quantitative Electroencephalogram mapping helped to provide an accurate assessment for placement of protocol as compared to behavioural checklist. Then, the researcher discussed all improvements in terms of behaviour modification in correlation with the changes of brainwave patterns. One of every 150 children born today in Malaysia has Autism (Malaysian Psychiatric Association, 2010). Their numbers are increasing; therefore, it is vital to do research on this disorder to improve the quality of life and reduce stress among parents and caregivers. Although there is no cure, appropriate management such as combination of neurofeedback and traditional method may foster normal development and reduce undesirable behaviours of ASD children. This study involved nine participants who were purposely selected from Kuching Autistic Association (KAA) with a diagnosis of having ASD symptoms by medical specialist. Their brain topography was obtained using qEEG brain mapping. Quantitative Electroencephalogram brain mapping followed by an average of 46 NFT sessions to monitor their brainwave. A neurofeedback protocol was designed to suppress the ratio of Theta and Alpha (4-10 Hz) to Beta (16-20) as well as to train the individual to normalize abnormal EEG frequencies. Neurofeedback protocols changed over time depending on participants’ mood, health condition and behaviour during training. Secondary qEEG recordings were made to see any brainwave alteration after neurofeedback training. There were series of observations for all participants before NFT as well as a series of observations after the NFT. Findings from qEEG mapping of this research were categorized under the third sub group - high Delta/Theta waves - as discovered by Michael Linden (2004) in his research on the four subtypes of autism. Quantitative Electroencephalogram discovers a pattern of high delta brainwave at prefrontal and frontal area, insufficient theta, alpha and beta brainwave in most of the brain region of ASD children. With regards to connectivity, main findings showed frontal lobe hyperconnectivity as well as hypoconnectivity of frontal region to other regions of the brain and diminished connectivity in language areas. The second qEEG session shows generally decreased Delta activity in frontal region of the brain, increased of theta, alpha and beta activity at most of the brain regions. The results have shown remarkable improvements in the participant’s speech, language, communication, sociability, cognitive and behaviour after five months. This research described that the brain lateralizations of ASD children were different from the brainwave pattern of the normal children and demonstrates the efficacy of NFT to help regulate the abnormal brainwaves and behaviour and improve the neuronal regulation of the brain as indicated by the normal features of the brainwaves. Universiti Malaysia Sarawak, (UNIMAS) 2015 Thesis http://ir.unimas.my/id/eprint/10760/ http://ir.unimas.my/id/eprint/10760/1/Electroencephalogram%20%28EEG%29%20Signature%20of%20Autism%20Spectrum%20Disorder%20%28ASD%29%20Children%20%2824pgs%29.pdf text en public http://ir.unimas.my/id/eprint/10760/8/Nurul%20Aina%20Mohd%20Mahayuddin%20ft.pdf text en validuser masters Universiti Malaysia Sarawak, (UNIMAS) Faculty of Cognitive Sciences and Human Development.
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English English
topic	Q Science (General)
spellingShingle	Q Science (General) Nurul Aina, bt Mohd Mahayuddin Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children
description	The purpose of this research was to explore, analyse and describe the brainwave pattern of Autism Spectrum Disorder (ASD) children using Quantitative Electroencephalogram (qEEG) and suggesting the right neurofeedback training (NFT) protocol. Quantitative Electroencephalogram primarily measures the electric potential field at the scalp surface. Quantitative Electroencephalogram mapping helped to provide an accurate assessment for placement of protocol as compared to behavioural checklist. Then, the researcher discussed all improvements in terms of behaviour modification in correlation with the changes of brainwave patterns. One of every 150 children born today in Malaysia has Autism (Malaysian Psychiatric Association, 2010). Their numbers are increasing; therefore, it is vital to do research on this disorder to improve the quality of life and reduce stress among parents and caregivers. Although there is no cure, appropriate management such as combination of neurofeedback and traditional method may foster normal development and reduce undesirable behaviours of ASD children. This study involved nine participants who were purposely selected from Kuching Autistic Association (KAA) with a diagnosis of having ASD symptoms by medical specialist. Their brain topography was obtained using qEEG brain mapping. Quantitative Electroencephalogram brain mapping followed by an average of 46 NFT sessions to monitor their brainwave. A neurofeedback protocol was designed to suppress the ratio of Theta and Alpha (4-10 Hz) to Beta (16-20) as well as to train the individual to normalize abnormal EEG frequencies. Neurofeedback protocols changed over time depending on participants’ mood, health condition and behaviour during training. Secondary qEEG recordings were made to see any brainwave alteration after neurofeedback training. There were series of observations for all participants before NFT as well as a series of observations after the NFT. Findings from qEEG mapping of this research were categorized under the third sub group - high Delta/Theta waves - as discovered by Michael Linden (2004) in his research on the four subtypes of autism. Quantitative Electroencephalogram discovers a pattern of high delta brainwave at prefrontal and frontal area, insufficient theta, alpha and beta brainwave in most of the brain region of ASD children. With regards to connectivity, main findings showed frontal lobe hyperconnectivity as well as hypoconnectivity of frontal region to other regions of the brain and diminished connectivity in language areas. The second qEEG session shows generally decreased Delta activity in frontal region of the brain, increased of theta, alpha and beta activity at most of the brain regions. The results have shown remarkable improvements in the participant’s speech, language, communication, sociability, cognitive and behaviour after five months. This research described that the brain lateralizations of ASD children were different from the brainwave pattern of the normal children and demonstrates the efficacy of NFT to help regulate the abnormal brainwaves and behaviour and improve the neuronal regulation of the brain as indicated by the normal features of the brainwaves.
format	Thesis
qualification_level	Master's degree
author	Nurul Aina, bt Mohd Mahayuddin
author_facet	Nurul Aina, bt Mohd Mahayuddin
author_sort	Nurul Aina, bt Mohd Mahayuddin
title	Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children
title_short	Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children
title_full	Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children
title_fullStr	Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children
title_full_unstemmed	Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children
title_sort	electroencephalogram (eeg) signature of autism spectrum disorder (asd) children
granting_institution	Universiti Malaysia Sarawak, (UNIMAS)
granting_department	Faculty of Cognitive Sciences and Human Development.
publishDate	2015
url	http://ir.unimas.my/id/eprint/10760/1/Electroencephalogram%20%28EEG%29%20Signature%20of%20Autism%20Spectrum%20Disorder%20%28ASD%29%20Children%20%2824pgs%29.pdf http://ir.unimas.my/id/eprint/10760/8/Nurul%20Aina%20Mohd%20Mahayuddin%20ft.pdf
_version_	1783728070437371904

Electroencephalogram (EEG) signature of autism spectrum disorder (ASD) children

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