Modeling the connections of brain regions in children with autism using cellular neural networks and electroencephalography analysis
•Brain regional connections in children with autism spectrum disorder (ASD) are analyzed.•Brain regional connections in ASD and control children are compared.•Brain connections are modeled using cellular neural networks and electroencephalography.•The proposed model successfully classifies ASD and c...
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| Published in | Artificial intelligence in medicine Vol. 89; pp. 40 - 50 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
01.07.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0933-3657 1873-2860 1873-2860 |
| DOI | 10.1016/j.artmed.2018.05.003 |
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| Abstract | •Brain regional connections in children with autism spectrum disorder (ASD) are analyzed.•Brain regional connections in ASD and control children are compared.•Brain connections are modeled using cellular neural networks and electroencephalography.•The proposed model successfully classifies ASD and control children.
The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method. |
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| AbstractList | •Brain regional connections in children with autism spectrum disorder (ASD) are analyzed.•Brain regional connections in ASD and control children are compared.•Brain connections are modeled using cellular neural networks and electroencephalography.•The proposed model successfully classifies ASD and control children.
The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method. The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method.The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method. The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method. |
| Author | Mohammadi, Mohammad Reza Sheikhani, Ali Teshnehlab, Mohammad Askari, Elham Setarehdan, Seyed Kamaledin |
| Author_xml | – sequence: 1 givenname: Elham surname: Askari fullname: Askari, Elham organization: Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran – sequence: 2 givenname: Seyed Kamaledin surname: Setarehdan fullname: Setarehdan, Seyed Kamaledin email: ksetareh@ut.ac.ir organization: Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran – sequence: 3 givenname: Ali surname: Sheikhani fullname: Sheikhani, Ali organization: Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran – sequence: 4 givenname: Mohammad Reza surname: Mohammadi fullname: Mohammadi, Mohammad Reza organization: Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran – sequence: 5 givenname: Mohammad surname: Teshnehlab fullname: Teshnehlab, Mohammad organization: Department of Control Engineering, K. N. Toosi University of Technology, Tehran, Iran |
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| SubjectTerms | Autism Cellular neural network Electroencephalography Emotiv Epoch |
| Title | Modeling the connections of brain regions in children with autism using cellular neural networks and electroencephalography analysis |
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