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Computational Model for Detection of Abnormal Brain Connections in Children With Autism 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: Journal of Integrative Neuroscience Published:2018


Abstract

In neuropsychological disorders significant abnormalities in brain connectivity are observed in some regions. A novel model demonstrates connectivity between different brain regions in children with autism. Wavelet decomposition is used to extract features such as relative energy and entropy from electroencephalograph signals. These features are used as input to a 3Dcellular neural network model that indicates brain connectivity. Results show significant differences and abnormalities in the left hemisphere, (p < 0:05) at electrodes AF3, F3, P7, T7, and O1 in the alpha band, AF3, F7, T7, and O1 in the beta band, and T7 and P7 in the gamma band for children with autism when compared with non-autistic controls. Abnormalities in the connectivity of frontal and parietal lobes and the relations of neighboring regions for all three bands (particularly the gamma band) were detected for autistic children. Evaluation demonstrated the alpha frequency band had the best level of distinction (96.6%) based on the values obtained from a cellular neural network that employed support vector machine methods. © 2018 IMR Press Limited. All rights reserved.
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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. Modeling the Connections of Brain Regions in Children With Autism Using Cellular Neural Networks and Electroencephalography Analysis, Artificial Intelligence in Medicine (2018)
3. Eeg Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities, Current Psychiatry Research and Reviews (2020)
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