Status of Quantitative EEG (QEEG) in Clinical Practice, 1994

Duffy, Frank H.; Hughes, John R.; Miranda, Fernando; Bernad, Peter G.; Cook, Patricia L.

doi:10.1177/155005949402500403

Cited by 105 publications

(65 citation statements)

References 87 publications

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“…Quantitative EEG (qEEG) measures are frequently applied in clinical research to compare spectral topographies recorded from individuals with identifiable pathology with those from a normative database (e.g. Duffy et al, 1981Duffy et al, , 1994. Since this approach is largely descriptive, it does not explicitly require a theoretical rationale regarding the nature of the underlying pathology.…”

Section: Quantification Of Eeg Rhythmsmentioning

confidence: 99%

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Tenke

Kayser

2005

Clinical Neurophysiology

166

225

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Objective: Definition of appropriate frequency bands and choice of recording reference limit the interpretability of quantitative EEG, which may be further compromised by distorted topographies or inverted hemispheric asymmetries when employing conventional (non-linear) power spectra. In contrast, fPCA factors conform to the spectral structure of empirical data, and a surface Laplacian (2-dimensional CSD) simplifies topographies by minimizing volume-conducted activity. Conciseness and interpretability of EEG and CSD fPCA solutions were compared for three common scaling methods. Methods: Resting EEG and CSD (30 channels, nose reference, eyes open/closed) from 51 healthy and 93 clinically-depressed adults were simplified as power, log power, and amplitude spectra, and summarized using unrestricted, Varimax-rotated, covariance-based fPCA. Results: Multiple alpha factors were separable from artifact and reproducible across subgroups. Power spectra produced numerous, sharplydefined factors emphasizing low frequencies. Log power spectra produced fewer, broader factors emphasizing high frequencies. Solutions for amplitude spectra showed optimal intermediate tuning, particularly when derived from CSD rather than EEG spectra. These solutions were topographically distinct, detecting multiple posterior alpha generators but excluding the dorsal surface of the frontal lobes. Instead a low alpha/theta factor showed a secondary topography along the frontal midline. Conclusions: CSD amplitude spectrum fPCA solutions provide simpler, reference-independent measures that more directly reflect neuronal activity. Significance: A new quantitative EEG approach affording spectral components is developed that closely parallels the concept of an ERP component in the temporal domain.

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Section: Quantification Of Eeg Rhythmsmentioning

confidence: 99%

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Tenke

Kayser

2005

Clinical Neurophysiology

166

225

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“…However, in this study we used the standard TQ-7 system in TLC protocol which is specific for depression, that is, asymmetry [18,25] or reversal category [13]. Regardless of the neurofeedback system used, several studies in the area of neurophysiology [13,22,24,26] have already shown that brains are organized by means of rhythmic oscillations expressed in different frequency ranges produced by the constant firing of the neurons. The constant changes in the patterns of these brain waves seem to be directly related to mental states and these changes are only possible due to neuronal neuroplasticity, which can be accessed using the electroencephalogram [27].…”

Section: Discussionmentioning

confidence: 99%

Treatment of Depression with Quantitative Electroencephalography(QEEG) of the TQ-7 Neuro-feedback System Increases the Level of Attention of Patients

Ribas¹,

Souza²,

Tulio³

et al. 2017

Journal of Neurological Disorders

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IntroductionDepression is characterized by a feeling of deep sadness associated with physiological and cognitive symptoms [1]. Both the ICD-10 and the American Psychiatric Association in their statistical manual of mental illness (DSM-V) characterize depression as a set of symptoms that include depressed mood (sadness, hopelessness), loss of interest and pleasure for previously satisfactory activities, and decreased energy, leading to a significant lack of enthusiasm that interferes with the life of the individual [2,3]. However, in relation to the etiology, most of the scientific community shares the idea that depression has multifactorial causes [4] that can originate from endogenous (neurobiological, genetic) [5], exogenous (psychosocial) [6] or traumatic factors (shock, letdown or a tumor) [7]. A biochemical alteration in the brain caused by a deficiency of serotonin [8], especially in the synaptic cleft, is implicated in the psychogenesis of neurobiological nature, possibly causing an imbalance of both mood and sense of well-being in the individual.This study focuses on problems of attention due to the possibility of accidents. Even though there are several theories related to the functioning of attention in the literature, Mateer & Mapou proposed a model that integrates all the previously proposed theories [9]. They established that attention is divided into two cognitive factors: AbstractIntroduction: Among the symptoms of depression, impairment in the level of attention has been a concern because of the risk of accidents.

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“…A statement by Duffy et al (1994) in a position paper of the American Medical EEG Association on QEEG still holds true today, particularly in the field of neurofeedback: "There is no single, agreed upon standard QEEG test battery . .…”

Section: Journal Of Neurotherapymentioning

confidence: 99%

Standards for the Use of Quantitative Electroencephalography (QEEG) in Neurofeedback: A Position Paper of the International Society for Neuronal Regulation

Hammond

Walker

Hoffman³

et al. 2004

Journal of Neurotherapy

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Status of Quantitative EEG (QEEG) in Clinical Practice, 1994

Cited by 105 publications

References 87 publications

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Treatment of Depression with Quantitative Electroencephalography(QEEG) of the TQ-7 Neuro-feedback System Increases the Level of Attention of Patients

Standards for the Use of Quantitative Electroencephalography (QEEG) in Neurofeedback: A Position Paper of the International Society for Neuronal Regulation

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