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Happe, Svenja; Anderer, P.; Gruber, Georg; Klösch, Gerhard; Saletu, B.; Zeitlhofer, J.

doi:10.1023/a:1019992523246

Cited by 46 publications

(7 citation statements)

References 31 publications

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“…Similar scalp distributions have been reported for spontaneous KCs (22) and SWS delta activity (23). The frontal distribution supports positron emission tomography (PET) (24) and high density EEG array (25) studies, implying a role for frontal cortex in the generation of delta activity during sleep.…”

Section: Introductionsupporting

confidence: 82%

The Impact of Alcoholism on Sleep Evoked Δ Frequency Responses

Colrain

Crowley²,

Nicholas

et al. 2009

Biological Psychiatry

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Background K-complexes (KC) are evoked delta frequency EEG responses during sleep that occur when large numbers of healthy cortical cells burst fire in a synchronized manner. KC amplitude and incidence are sensitive measures of normal healthy brain aging. Given the known neurodegenerative consequences of alcohol abuse it was hypothesized that alcoholism would be associated with further KC amplitude and incidence reductions. Methods 84 subjects (42 alcoholics) screened for medical, psychiatric and sleep problems, participated. The protocol involved the presentation of auditory stimuli during stage 2 sleep throughout a night in the laboratory. KCs were identified and averaged, to enable measurement of the P2, N550, and P900 peaks. Results Compared with controls, alcoholic men and women had lower KC incidence (p < .001) and P2 (P < .001), N550 (p < .05) and P900 (p < .05) amplitudes. There was a significant diagnosis by site interaction (p < .001) indicating the group difference was largest at frontal sites. Longer sobriety correlated with increased N550 amplitude (p < .01). Conclusions KC incidence and amplitude were negatively impacted in alcoholic men and women with exacerbation of the normal aging effects, particularly over frontal scalp regions. The observed relationship between improvements in KC measures and increased time of abstinence suggests that these measures may provide a useful marker of brain recovery with continued abstinence from alcohol.

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Section: Introductionsupporting

confidence: 82%

The Impact of Alcoholism on Sleep Evoked Δ Frequency Responses

Colrain

Crowley²,

Nicholas

et al. 2009

Biological Psychiatry

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“…The EEG changes along the anterior-posterior midline access have been reported many times and can be seen with just a few EEG electrodes (De Gennaro et al, 2001). Changes in the spectral patterns of EEG topography across sleep stages and during periods with spindles (Werth et al, 1997) and KCs (Happe et al, 2002) have also been reported before. For the purposes of the results that follow, Figure 3 serves two purposes: First, it demonstrates that at the level of raw signal, the data we used are consistent with what earlier works reported.…”

Section: Resultssupporting

confidence: 60%

Using MEG to Understand the Progression of Light Sleep and the Emergence and Functional Roles of Spindles and K-Complexes

Ioannides¹,

Liu²,

Poghosyan

et al. 2017

Front. Hum. Neurosci.

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We used tomographic analysis of MEG signals to characterize regional spectral changes in the brain at sleep onset and during light sleep. We identified two key processes that may causally link to loss of consciousness during the quiet or “core” periods of NREM1. First, active inhibition in the frontal lobe leads to delta and theta spectral power increases. Second, activation suppression leads to sharp drop of spectral power in alpha and higher frequencies in posterior parietal cortex. During NREM2 core periods, the changes identified in NREM1 become more widespread, but focal increases also emerge in alpha and low sigma band power in frontal midline cortical structures, suggesting reemergence of some monitoring of internal and external environment. Just before spindles and K-complexes (KCs), the hallmarks of NREM2, we identified focal spectral power changes in pre-frontal cortex, mid cingulate, and areas involved in environmental and internal monitoring, i.e., the rostral and sub-genual anterior cingulate. During both spindles and KCs, alpha and low sigma bands increases. Spindles emerge after further active inhibition (increase in delta power) of the frontal areas responsible for environmental monitoring, while in posterior parietal cortex, power increases in low and high sigma bands. KCs are correlated with increase in alpha power in the monitoring areas. These specific regional changes suggest strong and varied vigilance changes for KCs, but vigilance suppression and sharpening of cognitive processing for spindles. This is consistent with processes designed to ensure accurate and uncorrupted memory consolidation. The changes during KCs suggest a sentinel role: evaluation of the salience of provoking events to decide whether to increase processing and possibly wake up, or to actively inhibit further processing of intruding influences. The regional spectral patterns of NREM1, NREM2, and their dynamic changes just before spindles and KCs reveal an edge effect facilitating the emergence of spindles and KCs and defining the precise loci where they might emerge. In the time domain, the spindles are seen in widespread areas of the cortex just as reported from analysis of intracranial data, consistent with the emerging consensus of a differential topography that depends on the kind of memory stored.

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“…In our previous work, we have shown that the slow waves tend to originate from the frontal cortex and propagate toward the posterior cortex (see Fig. 4B–D in 20 ), similarly to the human slow wave 28 . Figure 5b compares the amplitude of slow waves in the anterior and posterior areas under different conditions, which is consistent with previous findings.…”

Section: Technical Validationsupporting

confidence: 51%

Nine-day continuous recording of EEG and 2-hour of high-density EEG under chronic sleep restriction in mice

Han

Kim

et al. 2022

Sci Data

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This work provides an EEG dataset collected from nine mice during the sleep deprivation (SD) paradigm for the sleep science community. It includes 9-day of continuous recording of the frontal and parietal EEG, accelerometer, and 2-hour of high-density EEG (HD-EEG) under SD and SD-free conditions. Eighteen hours of SD were conducted on 5 consecutive days. The HD-EEG data were saved in the EEGLAB format and stored as the brain imaging data structure (BIDS). These datasets can be used to (i) compare mouse HD-EEG to human HD-EEG, (ii) track oscillatory activities of the sleep EEG (e.g., slow waves, spindles) across the cortical regions under different conditions of sleep pressure, and (iii) investigate the cortical traveling waves in the mouse brain. We also provided Python code for basic analyses of this dataset, including the detection of slow waves and sleep spindles. We hope that our dataset will reveal hidden activities during sleep and lead to a better understanding of the functions and mechanisms of sleep.

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Cited by 46 publications

References 31 publications

The Impact of Alcoholism on Sleep Evoked Δ Frequency Responses

The Impact of Alcoholism on Sleep Evoked Δ Frequency Responses

Using MEG to Understand the Progression of Light Sleep and the Emergence and Functional Roles of Spindles and K-Complexes

Nine-day continuous recording of EEG and 2-hour of high-density EEG under chronic sleep restriction in mice

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