Beta Brain Waves as an Index of Alertness

Dustman, Robert E.; Boswell, Reed S.; Porter, Paul B.

doi:10.1126/science.137.3529.533

Cited by 43 publications

(13 citation statements)

References 6 publications

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“…However, the power difference between eyes open and eyes closed was less pronounced in the patient group. The normally observed reduction of alpha power in the eyes open condition is assumed to be due to the higher level of alertness and the prominence of beta-waves (Dustman et al, 1962). We hypothesize that an overall reduction of alertness in liver cirrhosis-patients might be responsible for the smaller power difference between eyes open and eyes closed in these patients.…”

Section: Discussionmentioning

confidence: 99%

Impaired evoked and resting-state brain oscillations in patients with liver cirrhosis as revealed by magnetoencephalography

Götz¹,

Huonker²,

Kranczioch³

et al. 2013

NeuroImage: Clinical

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A number of studies suggest that the clinical manifestation of neurological deficits in hepatic encephalopathy results from pathologically synchronized neuronal oscillations and altered oscillatory coupling. In the present study spontaneous and evoked oscillatory brain activities were analyzed jointly with established behavioral measures of altered visual oscillatory processing. Critical flicker and fusion frequencies (CFF, FUF) were measured in 25 patients diagnosed with liver cirrhosis and 30 healthy controls. Magnetoencephalography (MEG) data were collected at rest and during a visual task employing repetitive stimulation. Resting MEG and evoked fields were analyzed. CFF and FUF were found to be reduced in patients, providing behavioral evidence for deficits in visual oscillatory processing. These alterations were found to be related to resting brain activity in patients, namely that the lower the dominant MEG frequency at rest, the lower the CFF and FUF. An analysis of evoked fields at sensor level indicated that in comparison to normal controls, patients were not able to dynamically adapt to flickering visual stimulation. Evoked activity was also analyzed based on independent components (ICs) derived by independent component analysis. The similarity between the shape of each IC and an artificial sine function representing the stimulation frequency was tested via magnitude squared coherence. In controls, we observed a small number of components that correlated strongly with the sine function and a high number of ICs that did not correlate with the sine function. Interestingly, patient data were characterized by a high number of moderately correlating components. Taken together, these results indicate a fundamental divergence of the cerebral resonance activity in cirrhotic patients.

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Section: Discussionmentioning

confidence: 99%

Impaired evoked and resting-state brain oscillations in patients with liver cirrhosis as revealed by magnetoencephalography

Götz¹,

Huonker²,

Kranczioch³

et al. 2013

NeuroImage: Clinical

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“…However, the reliance on a subjective assessment approach which can be prone to patient and expert bias means that researchers have been trying to develop new ways to inform clinical diagnosis and treatment effectiveness using objective symptom biomarkers, with electroencephalography (EEG) being one method of interest (McLoughlin et al, 2014; Jeste et al, 2015; Olbrich et al, 2015). The approach that dominates the literature focuses on analyzing broad frequency bands in the EEG power spectrum termed delta, theta, alpha, beta, and gamma (Berger, 1929; Jasper and Andrews, 1936; Hoagland et al, 1937a,b; Dustman et al, 1962). This interpretation of the EEG signal in terms of spectral bands has its origins in the technical limitations of the pre-computer era of the 1930s and ‘40s when few other analytical options were available.…”

Section: Introductionmentioning

confidence: 99%

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

Newson¹,

Thiagarajan²

2019

Front. Hum. Neurosci.

563

432

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A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

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“…Low potential, fast EEG activity has also been associated with factors of stress, anxiety, and apprehension (Ulett et al, 1953;Johnson & Ulett, 1959). Moreover, reaction time studies by Lansing et al (1959), and by Dustman et al (1962), demonstrate that no-alpha EEG activities do not always represent the same kind of alertness.…”

Section: Resultsmentioning

confidence: 99%

Specificity of Eeg Photic Flicker Responses to Color as Related to Visual Imagery Ability

Brown¹

1966

Psychophysiology

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Two groups of subjects were selected from a previously studied population sample: a group of habitual visualizers, most of whom developed eye movements during recall of motion, and a group of non‐visualizers, most of whom did not. EEG following responses to red photic flicker differed markedly for the two groups, being diminished in visualizers but enhanced in non‐visualizers as compared to their EEG following responses to blue or green. Mental and visual imagery tasks induced significantly greater alpha blocking in visualizers than in non‐visualizers. The partial or complete desynchronization of on‐going rhythmic EEG activity suggests a lower threshold for EEG desynchronization for visualizers than for non‐visualizers. The augmented EEG following of non‐visualizers to red flicker appears to represent a different aspect of the same response continuum.

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Beta Brain Waves as an Index of Alertness

Cited by 43 publications

References 6 publications

Impaired evoked and resting-state brain oscillations in patients with liver cirrhosis as revealed by magnetoencephalography

Impaired evoked and resting-state brain oscillations in patients with liver cirrhosis as revealed by magnetoencephalography

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

Specificity of Eeg Photic Flicker Responses to Color as Related to Visual Imagery Ability

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