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Electroencephalograms in Diagnosis of Autism

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Comprehensive Guide to Autism

Abstract

This chapter is a state-of-the-art literature review of the EEG-based pathology and diagnosis of autism, in both resting condition and during tasks. With a methodological view the authors categorize the resting EEG-based methods into two classes, linear methods and nonlinear methods, and with a view of scale and conception, the authors categorize the methods into local and global organizations of the brain networks. The linear methods analyze the EEGs considering the brain as a linear system with linear connections and linear functions in each brain region. The power spectrum analysis, cross-correlation, and coherence functions are examples of the linear methods. In nonlinear methods the brain is considered as a complex system with nonlinear interactions among the neuronal regions, which is conceptually closer to the actual brain. Nonlinear methods have been developed primarily based on chaos theory, nonlinear science, and information theory. Fractality, entropy, complexity, and nonlinearity are examples of concepts in this approach which are quantified through various algorithms. Analysis of the brain network within or between specific regions is called the local organization-based analysis of the functional brain network, e.g., functional connectivity analysis of the brain. In contrast analyses of the global organization of the brain attempt to quantify the global properties of the whole functional connectivity brain network, e.g., small-worldness, scale-freeness, and complexity of the structure of the whole functional connectivity brain network.

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Authors and Affiliations

  1. Netherlands Institute for Neuroscience, Amsterdam, Netherlands

    Mehran Ahmadlou

  2. Neurological Surgery, 470 Hitchcock Hall 2070 Neil Avenue, Columbus, OH, USA

    Hojjat Adeli

Authors
  1. Mehran Ahmadlou
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  2. Hojjat Adeli
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Correspondence to Mehran Ahmadlou .

Editor information

Editors and Affiliations

  1. Department of Biomedical Sciences, University of Westminster, Faculty of Science & Technology, London, United Kingdom

    Vinood B. Patel

  2. Nutritional Sciences Division and Genomics Centre, King's College London, London, United Kingdom

    Victor R. Preedy

  3. Faculty of Society and Health, Buckinghamshire New University, Middlesex, United Kingdom

    Colin R. Martin

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Ahmadlou, M., Adeli, H. (2014). Electroencephalograms in Diagnosis of Autism. In: Patel, V., Preedy, V., Martin, C. (eds) Comprehensive Guide to Autism. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4788-7_204

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  • DOI: https://doi.org/10.1007/978-1-4614-4788-7_204

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-4787-0

  • Online ISBN: 978-1-4614-4788-7

  • eBook Packages: Behavioral Science

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