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Modeling the Connections of Brain Regions in Children With Autism Using Cellular Neural Networks and Electroencephalography Analysis Publisher Pubmed



Askari E1 ; Setarehdan SK2 ; Sheikhani A3 ; Mohammadi MR4 ; Teshnehlab M5
Authors
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Authors Affiliations
  1. 1. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
  2. 2. Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
  3. 3. Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
  4. 4. Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Department of Control Engineering, K. N. Toosi University of Technology, Tehran, Iran

Source: Artificial Intelligence in Medicine Published:2018


Abstract

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. © 2018 Elsevier B.V.
Related Docs
1. Designing a Model to Detect the Brain Connections Abnormalities in Children With Autism Using 3D-Cellular Neural Networks, Journal of Integrative Neuroscience (2018)
2. Computational Model for Detection of Abnormal Brain Connections in Children With Autism, Journal of Integrative Neuroscience (2018)
Experts (# of related papers)
Mohammad Reza Mohammadi (2)