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Computational EEG Analysis pp 149–175Cite as

Computational EEG Analysis for the Diagnosis of Psychiatric Illnesses

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Abstract

Electroencephalography (EEG) holds promise as a tool to diagnose psychiatric disorders. While it has some major advantages such as high temporal resolution, relative affordability, and easy accessibility, even its shortcomings are being addressed through the advancement in its analysis. As a result, numerous researches have been examining EEG components as potential biomarkers of various psychiatric diseases. In this chapter, we discuss several promising EEG markers, ranging from resting state EEG to stimuli induced ERP components, from electrodes level to source level, and from band power to functional connectivity networks. In addition, we present the findings of previous studies with an emphasis on how each EEG component vary depending of the specific psychiatric illnesses. The psychiatric disorders discussed in this chapter are (1) schizophrenia, (2) bipolar disorder, (3) major depressive disorder, (4) anxiety related disorders (e.g., post-traumatic stress disorder and obsessive compulsive disorder) and (5) disorders related to cognitive impairments (e.g., dementia and minimal cognitive impairment. Lastly, we introduce how the limitations of EEG, which mostly occur as a byproduct of sensor-level analysis, can be addressed through source-level analysis.

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Acknowledgments

This research was supported by the Brain Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT & Future Planning (NRF-2015M3C7A1028252), the Korea Science and Engineering Foundation (KOSEF), funded by the Korean government (NRF-2018R1A2A2A05018505), and by the 2017 creative research program of Inje University.

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  1. Department of Psychiatry, Inje University, Ilsan-Paik Hospital, Goyang, Republic of Korea

    Seung-Hwan Lee

  2. Clinical Emotion and Cognition Research Laboratory, Inje University, Goyang, South Korea

    Seung-Hwan Lee & Yeonsoo Park

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Correspondence to Seung-Hwan Lee .

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  1. Department of Biomedical Engineering, Hanyang University, Seongdong-gu, Seoul, Korea (Republic of)

    Chang-Hwan Im

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Lee, SH., Park, Y. (2018). Computational EEG Analysis for the Diagnosis of Psychiatric Illnesses. In: Im, CH. (eds) Computational EEG Analysis. Biological and Medical Physics, Biomedical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-0908-3_7

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