Literature DB >> 20006545

Independent component approach to the analysis of EEG recordings at early stages of depressive disorders.

Vera A Grin-Yatsenko1, Ineke Baas, Valery A Ponomarev, Juri D Kropotov.   

Abstract

OBJECTIVE: A modern approach for blind source separation of electrical activity represented by Independent Components Analysis (ICA) was used for QEEG analysis in depression.
METHODS: The spectral characteristics of the resting EEG in 111 adults in the early stages of depression and 526 non-depressed subjects were compared between groups of patients and healthy controls using a combination of ICA and sLORETA methods.
RESULTS: Comparison of the power of independent components in depressed patients and healthy controls have revealed significant differences between groups for three frequency bands: theta (4-7.5Hz), alpha (7.5-14Hz), and beta (14-20Hz) both in Eyes closed and Eyes open conditions. An increase in slow (theta and alpha) activity in depressed patients at parietal and occipital sites may reflect a decreased cortical activation in these brain regions, and a diffuse enhancement of beta power may correlate with anxiety symptoms playing an important role on the onset of depressive disorder.
CONCLUSIONS: ICA approach used in the present study allowed us to localize the EEG spectra differences between the two groups. SIGNIFICANCE: A relatively rare approach which uses the ICA spectra for comparison of the quantitative parameters of EEG in different groups of patients/subjects allows to improve an accuracy of measurement.

Entities:  

Mesh:

Year:  2009        PMID: 20006545     DOI: 10.1016/j.clinph.2009.11.015

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  29 in total

1.  Dynamic changes of ICA-derived EEG functional connectivity in the resting state.

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2.  Decreased thalamo-cortical connectivity by alteration of neural information flow in theta oscillation in depression-model rats.

Authors:  Chenguang Zheng; Meina Quan; Tao Zhang
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3.  Likelihood-based population independent component analysis.

Authors:  Ani Eloyan; Ciprian M Crainiceanu; Brian S Caffo
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Authors:  Fleur M Howells; Dan J Stein; Vivienne A Russell
Journal:  Metab Brain Dis       Date:  2012-03-08       Impact factor: 3.584

5.  α Power, α asymmetry and anterior cingulate cortex activity in depressed males and females.

Authors:  Natalia Jaworska; Pierre Blier; Wendy Fusee; Verner Knott
Journal:  J Psychiatr Res       Date:  2012-08-28       Impact factor: 4.791

6.  Mild Depression Detection of College Students: an EEG-Based Solution with Free Viewing Tasks.

Authors:  Xiaowei Li; Bin Hu; Ji Shen; Tingting Xu; Martyn Retcliffe
Journal:  J Med Syst       Date:  2015-10-21       Impact factor: 4.460

7.  Classification of Depression Patients and Normal Subjects Based on Electroencephalogram (EEG) Signal Using Alpha Power and Theta Asymmetry.

Authors:  Shalini Mahato; Sanchita Paul
Journal:  J Med Syst       Date:  2019-12-13       Impact factor: 4.460

8.  Childhood Trauma is Associated with Altered Cortical Arousal: Insights from an EEG Study.

Authors:  Fleur Margaret Howells; Dan J Stein; Vivienne A Russell
Journal:  Front Integr Neurosci       Date:  2012-12-24

9.  Psychoacoustic tinnitus loudness and tinnitus-related distress show different associations with oscillatory brain activity.

Authors:  Tobias Balkenhol; Elisabeth Wallhäusser-Franke; Wolfgang Delb
Journal:  PLoS One       Date:  2013-01-10       Impact factor: 3.240

10.  A review of electroencephalographic changes in diabetes mellitus in relation to major depressive disorder.

Authors:  Anusha Baskaran; Roumen Milev; Roger S McIntyre
Journal:  Neuropsychiatr Dis Treat       Date:  2013-01-17       Impact factor: 2.570

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