The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders

Background. An electroencephalogram (EEG) is a simple and widely used assessment tool that allows one to analyze the bioelectric activity of the brain. As a result, one can observe brain waves with different frequencies and amplitudes that correspond to the temporary synchronization of different par...

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Main Authors: Kamil Jonak, Arkadiusz Syta, Hanna Karakuła-Juchnowicz, Paweł Krukow
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Brain Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3425/10/6/380
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author Kamil Jonak
Arkadiusz Syta
Hanna Karakuła-Juchnowicz
Paweł Krukow
author_facet Kamil Jonak
Arkadiusz Syta
Hanna Karakuła-Juchnowicz
Paweł Krukow
author_sort Kamil Jonak
collection DOAJ
description Background. An electroencephalogram (EEG) is a simple and widely used assessment tool that allows one to analyze the bioelectric activity of the brain. As a result, one can observe brain waves with different frequencies and amplitudes that correspond to the temporary synchronization of different parts of the brain. Synchronization patterns may be changed by almost any type of pathological conditions, such as psychiatric diseases and structural abnormalities of the brain tissue. In various neuropsychiatric disorders, the coordination of cortical activity may be decreased or enhanced as a result of neurobiological compensatory mechanisms. Methods. In this paper, we analyzed the EEG signals in resting-state condition, with reference to three patients with a similar set of psychopathological symptoms typical for the first psychotic episode, but with different functional and structural neural basis of the disease. Additionally, those patients were compared with a demographically matched healthy individual. We used the non-linear method of time series analysis based on the recurrences of states, to verify whether functional connectivity configurations assessed with recurrence method will qualitatively distinguish patients from a healthy subject, but also differentiate patients from each other. Results. Obtained results confirmed that the connectivity architecture mapped with the recurrence analysis substantially differentiated all participants from each other. An applied analysis additionally showed the specificity of cortical desynchronization and over-synchronization matched to the psychiatric or neurological basis of the disease. Despite this encouraging finding, group-oriented studies are needed to corroborate our qualitative results, based only on a series of clinical case studies.
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spelling doaj.art-9cbc330f6b1c4b299d0d429e0548789c2023-11-20T04:01:01ZengMDPI AGBrain Sciences2076-34252020-06-0110638010.3390/brainsci10060380The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric DisordersKamil Jonak0Arkadiusz Syta1Hanna Karakuła-Juchnowicz2Paweł Krukow3Department of Psychiatry, Psychotherapy and Early Intervention, Medical University of Lublin, 20-439 Lublin, PolandMechanical Engineering Faculty, Lublin University of Technology, Nadbystrzycka 38 D, 20-618 Lublin, PolandDepartment of Psychiatry, Psychotherapy and Early Intervention, Medical University of Lublin, 20-439 Lublin, PolandDepartment of Clinical Neuropsychiatry, Medical University of Lublin, ul. Gluska 1, 20-439 Lublin, PolandBackground. An electroencephalogram (EEG) is a simple and widely used assessment tool that allows one to analyze the bioelectric activity of the brain. As a result, one can observe brain waves with different frequencies and amplitudes that correspond to the temporary synchronization of different parts of the brain. Synchronization patterns may be changed by almost any type of pathological conditions, such as psychiatric diseases and structural abnormalities of the brain tissue. In various neuropsychiatric disorders, the coordination of cortical activity may be decreased or enhanced as a result of neurobiological compensatory mechanisms. Methods. In this paper, we analyzed the EEG signals in resting-state condition, with reference to three patients with a similar set of psychopathological symptoms typical for the first psychotic episode, but with different functional and structural neural basis of the disease. Additionally, those patients were compared with a demographically matched healthy individual. We used the non-linear method of time series analysis based on the recurrences of states, to verify whether functional connectivity configurations assessed with recurrence method will qualitatively distinguish patients from a healthy subject, but also differentiate patients from each other. Results. Obtained results confirmed that the connectivity architecture mapped with the recurrence analysis substantially differentiated all participants from each other. An applied analysis additionally showed the specificity of cortical desynchronization and over-synchronization matched to the psychiatric or neurological basis of the disease. Despite this encouraging finding, group-oriented studies are needed to corroborate our qualitative results, based only on a series of clinical case studies.https://www.mdpi.com/2076-3425/10/6/380neuroinformaticsnon-linear time series analysisEEGschizophreniawhite matter
spellingShingle Kamil Jonak
Arkadiusz Syta
Hanna Karakuła-Juchnowicz
Paweł Krukow
The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders
Brain Sciences
neuroinformatics
non-linear time series analysis
EEG
schizophrenia
white matter
title The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders
title_full The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders
title_fullStr The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders
title_full_unstemmed The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders
title_short The Clinical Application of EEG-Signals Recurrence Analysis as a Measure of Functional Connectivity: Comparative Case Study of Patients with Various Neuropsychiatric Disorders
title_sort clinical application of eeg signals recurrence analysis as a measure of functional connectivity comparative case study of patients with various neuropsychiatric disorders
topic neuroinformatics
non-linear time series analysis
EEG
schizophrenia
white matter
url https://www.mdpi.com/2076-3425/10/6/380
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