Frontiers in Neuroinformatics (May 2018)

New Protocol for Quantitative Analysis of Brain Cortex Electroencephalographic Activity in Patients With Psychiatric Disorders

  • Grzegorz M. Wojcik,
  • Jolanta Masiak,
  • Andrzej Kawiak,
  • Piotr Schneider,
  • Lukasz Kwasniewicz,
  • Nikodem Polak,
  • Anna Gajos-Balinska

DOI
https://doi.org/10.3389/fninf.2018.00027
Journal volume & issue
Vol. 12

Abstract

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The interview is still the main and most important tool in psychiatrist's work. The neuroimaging methods such as CT or MRI are widely used in other fields of medicine, for instance neurology. However, psychiatry lacks effective quantitative methods to support of diagnosis. A novel neuroinformatic approach to help clinical patients by means of electroencephalographic technology in order to build foundations for finding neurophysiological biomarkers of psychiatric disorders is proposed. A cohort of 30 right-handed patients (21 males, 9 females) with psychiatric disorders (mainly with panic and anxiety disorder, Asperger syndrome as well as with phobic anxiety disorders, schizophrenia, bipolar affective disorder, obsessive-compulsive disorder, nonorganic hypersomnia, and moderate depressive episode) were examined using the dense array EEG amplifier in the P300 experiment. The results were compared with the control group of 30 healthy, right-handed male volunteers. The quantitative analysis of cortical activity was conducted using the sLORETA source localization algorithm. The most active Brodmann Areas were pointed out and a new quantitative observable of electrical charge flowing through the selected Brodmann Area is proposed. The precise methodology and research protocol for collecting EEG data as well as the roadmap of future investigations in this area are presented. The essential result of this study is the idea proven by the initial results of our experiments that it is possible to determine quantitatively biomarkers of particular psychiatric disorders in order to support the process of diagnosis and hopefully choose most appropriate medical treatment later.

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