Ekaterina Proshina, Olga Martynova, Galina Portnova, Guzal Khayrullina, Olga Sysoeva
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We assumed that the LRTC patterns will allow us to compare measures of brain cortical balance of excitation and inhibition in OCD and MDD, which will be useful in the area of differential diagnosis.</p></sec><sec><title>Methods</title><p>In this study, we used the 64-channel resting state EEG of 29 MDD participants, 26 OCD participants, and a control group of 37 volunteers. Detrended fluctuation analyzes was used to assess LRTC.</p></sec><sec><title>Results</title><p>Our results indicate that all scaling exponents of the three subject groups exhibited persistent LRTC of EEG oscillations. There was a tendency for LRTC to be higher in disorders than in controls, but statistically significant differences were found between the OCD and control groups in the entire frontal and left parietal occipital areas, and between the MDD and OCD groups in the middle and right frontal areas.</p></sec><sec><title>Discussion</title><p>We believe that these results indicate abnormalities in the inhibitory and excitatory neurotransmitter systems, predominantly affecting areas related to executive functions.</p></sec>","PeriodicalId":12462,"journal":{"name":"Frontiers in Neuroinformatics","volume":"15 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder\",\"authors\":\"Ekaterina Proshina, Olga Martynova, Galina Portnova, Guzal Khayrullina, Olga Sysoeva\",\"doi\":\"10.3389/fninf.2024.1339590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<sec><title>Introduction</title><p>Mental disorders are a significant concern in contemporary society, with a pressing need to identify biological markers. Long-range temporal correlations (LRTC) of brain rhythms have been widespread in clinical cohort studies, especially in major depressive disorder (MDD). However, research on LRTC in obsessive-compulsive disorder (OCD) is severely limited. Given the high co-occurrence of OCD and MDD, we conducted a comparative LRTC investigation. We assumed that the LRTC patterns will allow us to compare measures of brain cortical balance of excitation and inhibition in OCD and MDD, which will be useful in the area of differential diagnosis.</p></sec><sec><title>Methods</title><p>In this study, we used the 64-channel resting state EEG of 29 MDD participants, 26 OCD participants, and a control group of 37 volunteers. Detrended fluctuation analyzes was used to assess LRTC.</p></sec><sec><title>Results</title><p>Our results indicate that all scaling exponents of the three subject groups exhibited persistent LRTC of EEG oscillations. 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Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder
Introduction
Mental disorders are a significant concern in contemporary society, with a pressing need to identify biological markers. Long-range temporal correlations (LRTC) of brain rhythms have been widespread in clinical cohort studies, especially in major depressive disorder (MDD). However, research on LRTC in obsessive-compulsive disorder (OCD) is severely limited. Given the high co-occurrence of OCD and MDD, we conducted a comparative LRTC investigation. We assumed that the LRTC patterns will allow us to compare measures of brain cortical balance of excitation and inhibition in OCD and MDD, which will be useful in the area of differential diagnosis.
Methods
In this study, we used the 64-channel resting state EEG of 29 MDD participants, 26 OCD participants, and a control group of 37 volunteers. Detrended fluctuation analyzes was used to assess LRTC.
Results
Our results indicate that all scaling exponents of the three subject groups exhibited persistent LRTC of EEG oscillations. There was a tendency for LRTC to be higher in disorders than in controls, but statistically significant differences were found between the OCD and control groups in the entire frontal and left parietal occipital areas, and between the MDD and OCD groups in the middle and right frontal areas.
Discussion
We believe that these results indicate abnormalities in the inhibitory and excitatory neurotransmitter systems, predominantly affecting areas related to executive functions.
期刊介绍:
Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide.
Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states.
Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.