Intercorrelations between Different Computer-Based Measures of the EEG Alpha Amplitude and Its Variability over Time and Their Validity in Differentiating Healthy Volunteers from Depressed Patients1

Knorring, Lars von; Perris, C.; Goldstein, Leonide; Kemali, D.; Monakhov, K.; Vacca, Laura

doi:10.1159/000408530

Cited by 23 publications

(8 citation statements)

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“…Our findings seem inconsistent with a bulk of literature pointing to increased left frontal alpha (Allen et al, 1993;Davidson et al, 1985;Henriques and Davidson, 1990;Schaffer et al, 1983) or bilaterally increased frontal alpha (Brenner et al, 1988;John et al, 1988;Lieber and Newbury, 1988;Schaffer et al, 1983;von Knorring et al, 1983) in depression, which, according to the authors, reflect frontal hypoactivity in this disorder. However, some other studies (Flor-Henry et al, 2004;Reid et al, 1998) also have not found prevalence in alpha activity in the left frontal area in depressed participants.…”

Section: Discussioncontrasting

confidence: 99%

EEG Power Spectra at Early Stages of Depressive Disorders

Grin-Yatsenko

Baas²,

Пономарев³

et al. 2009

Journal of Clinical Neurophysiology

115

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In previous quantitative EEG studies of depression, mostly patients with a lifetime history of depressive disorders were reported. This study examined quantitative EEG parameters obtained in the early stages of depression in comparison with age-matched healthy controls. EEG was recorded using two different montages in eyes closed and eyes open resting states. A significant increase in spectrum power in theta (4-7.5 Hz), alpha (7.5-14 Hz), and beta (14-20 Hz) frequency bands was found in depressed patients at parietal and occipital sites, both in eyes closed and eyes open conditions. These results suggest that an increase in slow (theta and alpha) activity in the EEG pattern may reflect a decreased cortical activation in these brain regions. Enhancement of beta power may correlate with anxiety symptoms that most likely play an important role on the onset of depressive disorder.

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Section: Discussioncontrasting

confidence: 99%

EEG Power Spectra at Early Stages of Depressive Disorders

Grin-Yatsenko

Baas²,

Пономарев³

et al. 2009

Journal of Clinical Neurophysiology

115

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“…For example, elevated EEG alpha activity during resting has been commonly observed [26]. Similarly, elevated absolute alpha power has been reported in the literature [27][28][29][30], while other studies have described increases in the relative power [31,32]. This increase in the EEG activity was commonly observed in frontal, parietal [28,33] and occipital areas [34].…”

Section: Aberrant Activations Including Eeg Frequency Bandsmentioning

confidence: 57%

“…Electrophysiological signals contain information about neural activities inside the brain at different frequencies, which range from delta (0.4-5 Hz), theta (5-8 Hz), alpha (8)(9)(10)(11)(12), low beta (12)(13)(14)(15)(16)(17)(18), high beta (19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) and gamma . Electrophysiological signals can be helpful during the diagnosis or quantification of physiological states.…”

Section: Introductionmentioning

confidence: 99%

Review on EEG and ERP predictive biomarkers for major depressive disorder

Mumtaz

Malik

Yasin

et al. 2015

Biomedical Signal Processing and Control

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“…In MDD a consistent finding is an elevated absolute [66,67,68,69,70] or relative alpha power [71,72] at mainly parietal and frontal [68,73] or occipital sites [74]. The reason that some studies did not find alpha power differences between patients and HCs [75,76] or found decreased (relative) alpha activity in comparison to other patient groups [77] might be related to differences of recording periods, where shorter recording periods prevent the differences described above [38,39] in vigilance regulation to occur (e.g.…”

Section: Biomarkersmentioning

confidence: 85%

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

2015

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Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.

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Intercorrelations between Different Computer-Based Measures of the EEG Alpha Amplitude and Its Variability over Time and Their Validity in Differentiating Healthy Volunteers from Depressed Patients1

Cited by 23 publications

References 0 publications

EEG Power Spectra at Early Stages of Depressive Disorders

EEG Power Spectra at Early Stages of Depressive Disorders

Review on EEG and ERP predictive biomarkers for major depressive disorder

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

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