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Research About Alpha EEG Asymmetry and Self-consciousness in Depression

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Brain Informatics and Health (BIH 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9919))

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Abstract

Depressive disorders shows an alpha EEG asymmetry with higher activation in the left anterior brain. This phenomenon might be associated with the strengthened negative activities in the right side of the brain, especially the information related to self-concept. However, it is absent of direct evidence to support the relationship between the alpha EEG asymmetry and self-concept, and it is not clear what the variation of the correlation between the two factors in depressive disorders. To investigate the issues, we collected the resting EEG data with eye-closed and the self-consciousness level data to compare the relationship between alpha EEG asymmetry and self-concept in depression patients and healthy controls. Results show that both the two groups have strong correlations between the self-consciousness and alpha asymmetry in the brain, but differed in the correlation patterns. Depressions show that self-consciousness is correlated with the more anterior alpha EEG asymmetry in the brain, while the healthy group correlate with the more posterior alpha asymmetry. These results indicate that the impairment of the correlation between self-concept and alpha asymmetry in depressive disorders might be a biomarker of the disease to be considered in future study.

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Acknowledgments

This work was supported by the National Basic Research Program of China (2014CB744600), International Science and Technology Cooperation Program of China (2013DFA32180), National Natural Science Foundation of China (61272345), and also supported by Beijing Municipal Commission of Education, Beijing International Collaboration Base on Brain Informatics and Wisdom Services and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics.

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Authors and Affiliations

  1. Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, 100124, China

    Xiaomeng Ma, Minghui Zhang, Jialiang Guo & Haiyan Zhou

  2. The International WIC Institute, Beijing University of Technology, Beijing, China

    Xiaomeng Ma, Minghui Zhang, Jialiang Guo & Haiyan Zhou

  3. The Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing, China

    Xiaomeng Ma, Minghui Zhang, Jialiang Guo & Haiyan Zhou

  4. The Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China

    Xiaomeng Ma, Minghui Zhang, Jialiang Guo & Haiyan Zhou

  5. Mood Disorders Center and China Clinical Research Center for Mental Disorders, Beijing Anding Hospital Capital Medical University, Beijing, China

    Jie Yang, Lei Feng & Gang Wang

Authors
  1. Xiaomeng Ma
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  2. Minghui Zhang
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  3. Jialiang Guo
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  4. Haiyan Zhou
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  5. Jie Yang
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  6. Lei Feng
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  7. Gang Wang
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Corresponding author

Correspondence to Haiyan Zhou .

Editor information

Editors and Affiliations

  1. George Mason University, Fairfax, Virginia, USA

    Giorgio A. Ascoli

  2. Department of Modeling, Analysis and Theory, Allen Institute for Brain Science, Seattle, Washington, USA

    Michael Hawrylycz

  3. University of Nebraska Omaha, Omaha, Nebraska, USA

    Hesham Ali

  4. Information Science and Technology, University of Nebraska Omaha, Omaha, Nebraska, USA

    Deepak Khazanchi

  5. College of Information Sciences and Technology, University of Nebraska Omaha, Omaha, Nebraska, USA

    Yong Shi

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© 2016 Springer International Publishing AG

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Ma, X. et al. (2016). Research About Alpha EEG Asymmetry and Self-consciousness in Depression. In: Ascoli, G., Hawrylycz, M., Ali, H., Khazanchi, D., Shi, Y. (eds) Brain Informatics and Health. BIH 2016. Lecture Notes in Computer Science(), vol 9919. Springer, Cham. https://doi.org/10.1007/978-3-319-47103-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-47103-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47102-0

  • Online ISBN: 978-3-319-47103-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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