scholarly journals P.128 Quantitative EEG Detects REM Sleep Microstructure

2021 ◽  
Vol 48 (s3) ◽  
pp. S56-S56
Author(s):  
D Toutant ◽  
M Ng
Keyword(s):  
Eye Movements ◽  
Rem Sleep ◽  
Quantitative Eeg ◽  
Artifact Reduction ◽  
Proof Of Concept ◽  
Rapid Eye Movement Sleep ◽  
Artifact Detection ◽  
Eeg Recordings ◽  
Sleep Microstructure ◽  
Epilepsy Monitoring

Background: Rapid eye movement sleep (REM) is divided into phasic and tonic microstates. Phasic REM is defined by presence of REMs with reportedly greater antiepileptic effect. We assessed whether quantitative EEG (QEEG) software can detect REM microstates. Methods: We applied artifact reduction and detection trends from QEEG software (Persyst 14) on 18 patients undergoing 30 day-night high density EEG recordings in the epilepsy monitoring unit. We identified phasic REM as 10-second epochs of previously human-scored REM that demonstrated presence of either vertical or horizontal eye movements on the QEEG artifact detection panel. Remaining epochs were identified as tonic REM. Results: Out of 91.2 average minutes of REM (range 24.5-167.5) per recording, a mean of 2.5% (range 0-18.9%) demonstrated eye movements intensive enough for QEEG artifact detection to be identified as phasic REM. On average, only 40% (range 0-500%) of eye movements per recording was flagged as vertical. Conclusions: These findings provide proof-of-concept that QEEG can automatically assess REM microstructure by readily detecting phasic and tonic REM. These findings also confirm that most REMs are horizontal. Having the ability to easily and automatically detect phasic versus tonic REM can help further future studies examining the antiepileptic effect of REM sleep.

scholarly journals Breakthrough spikes in rapid eye movement sleep from the epilepsy monitoring unit are associated with peak seizure frequency

SLEEP ◽  
2019 ◽  
Vol 43 (5) ◽  
Author(s):  
Marna B McKenzie ◽  
Michelle-Lee Jones ◽  
Aoife O’Carroll ◽  
Demitre Serletis ◽  
Leigh Anne Shafer ◽  
...  
Keyword(s):  
Eye Movement ◽  
Seizure Frequency ◽  
Epileptiform Activity ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Patient Reported ◽  
Eeg Recordings ◽  
Epilepsy Monitoring

Abstract Study Objectives Rapid eye movement sleep (REM) usually suppresses interictal epileptiform discharges (IED) and seizures. However, breakthrough IEDs in REM sometimes continue. We aimed to determine if the amount of IED and seizures in REM, or REM duration, is associated with clinical trajectories. Methods Continuous electroencephalogram (EEG) recordings from the epilepsy monitoring unit (EMU) were clipped to at least 3 h of concatenated salient findings per day including all identified REM. Concatenated EEG files were analyzed for nightly REM duration and the “REM spike burden” (RSB), defined as the proportion of REM occupied by IED or seizures. Patient charts were reviewed for clinical data, including patient-reported peak seizure frequency. Logistic and linear regressions were performed, as appropriate, to explore associations between two explanatory measures (duration of REM and RSB) and six indicators of seizure activity (clinical trajectory outcomes). Results The median duration of REM sleep was 43.3 (IQR 20.9–73.2) min per patient per night. 59/63 (93.7%) patients achieved REM during EMU admission. 39/59 (66.1%) patients had breakthrough IEDs or seizures in REM with the median RSB at 0.7% (IQR 0%–8.4%). Every 1% increase in RSB was associated with 1.69 (95% CI = 0.47–2.92) more seizures per month during the peak seizure period of one’s epilepsy (p = 0.007). Conclusions Increased epileptiform activity during REM is associated with increased peak seizure frequency, suggesting an overall poorer epilepsy trajectory. Our findings suggest that RSB in the EMU is a useful biomarker to help guide about what to expect over the course of one’s epilepsy.

Differential activation within costal diaphragm during rapid-eye-movement sleep in cats

1991 ◽  
Vol 70 (3) ◽  
pp. 1194-1200 ◽  
Author(s):  
J. C. Hendricks ◽  
L. R. Kline
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Rem Sleep ◽  
Slow Wave Sleep ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Differential Activation ◽  
Sleep Period ◽  
Spike Patterns ◽  
Respiratory Generator

Simultaneous recordings of the diaphragmatic electromyogram (EMG) were made from two separate regions of the costal diaphragm in six normal cats. The diaphragmatic activities were always synchronous and the amplitudes and rates of rise were similar during slow-wave sleep. In contrast, during natural rapid-eye-movement (REM) sleep, different activity was often present in the two leads. These differences were in the time of onset and offset, as well as in the amplitude and spike patterns, and occurred in approximately 5-20% of the diaphragmatic bursts averaged over the entire REM sleep period. With respect to eye movement density, the rate of differential activation was higher during periods of high density (26%) than in the absence of eye movements (1%) in the four animals for which these data were available. Differential activation of portions of the costal diaphragm is apparently a normal event of REM sleep. This could result from descending state-specific phasic neuronal activity that bypasses the medullary respiratory generator. Differential activation of portions of the diaphragm could contribute to disordered ventilation during REM sleep.

REM sleep burst neurons, PGO waves, and eye movement information

1983 ◽  
Vol 50 (4) ◽  
pp. 784-797 ◽  
Author(s):  
J. P. Nelson ◽  
R. W. McCarley ◽  
J. A. Hobson
Keyword(s):  
Eye Movements ◽  
Visual System ◽  
Eye Movement ◽  
Rem Sleep ◽  
Rapid Eye Movement Sleep ◽  
Generation System ◽  
Rapid Eye Movements ◽  
Midbrain Neurons ◽  
Burst Neuron ◽  
Pgo Waves

Pontogeniculooccipital (PGO) waves appeared almost simultaneously in both lateral geniculate nuclei (LGB), but in each case on had a larger amplitude and preceded the other by a few milliseconds. The larger, earlier wave is called the primary wave. Primary waves were found to appear with equal frequency in each LGB. During rapid eye movement sleep (REM sleep), LGB primary waves were ipsilateral to the direction of rapid eye movements. During REM sleep a group of cat midbrain neurons, which we call PGO burst cells, fired in stereotyped bursts at fixed latencies before ipsilateral primary waves, but they almost never fired bursts when the primary waves were contralateral. PGO burst neuron discharge also correlated with the direction of rapid eye movements during REM sleep. In wakefulness, PGO burst cells fired single spikes, not bursts, which had some correlation with LGB waves when averaged by computer. The results suggest that PGO burst cells are output elements in the PGO wave-generation system ad that PGO waves convey eye movement information to the sensory visual system in REM sleep. They also may have a role in the production of saccade-related waves in the visual system during wakefulness.

scholarly journals Sounding It Out: Auditory Stimulation and Overnight Memory Processing

2021 ◽  
Author(s):  
Marcus O. Harrington ◽  
Scott A. Cairney
Keyword(s):  
Rem Sleep ◽  
Memory Consolidation ◽  
Slow Wave Sleep ◽  
Auditory Stimulation ◽  
Theta Oscillations ◽  
Neural Oscillations ◽  
Healthy Children ◽  
Factors Affecting ◽  
Memory Processing ◽  
Eeg Recordings

Abstract Purpose of Review Auditory stimulation is a technique that can enhance neural oscillations linked to overnight memory consolidation. In this review, we evaluate the impacts of auditory stimulation on the neural oscillations of sleep and associated memory processes in a variety of populations. Recent Findings Cortical EEG recordings of slow-wave sleep (SWS) are characterised by two cardinal oscillations: slow oscillations (SOs) and sleep spindles. Auditory stimulation delivered in SWS enhances SOs and phase-coupled spindle activity in healthy children and adults, children with ADHD, adults with mild cognitive impairment and patients with major depression. Under certain conditions, auditory stimulation bolsters the benefits of SWS for memory consolidation, although further work is required to fully understand the factors affecting stimulation-related memory gains. Recent work has turned to rapid eye movement (REM) sleep, demonstrating that auditory stimulation can be used to manipulate REM sleep theta oscillations. Summary Auditory stimulation enhances oscillations linked to overnight memory processing and shows promise as a technique for enhancing the memory benefits of sleep.

Walking by Thinking: The Brainwaves Are Crucial, Not the Muscles!

2006 ◽  
Vol 15 (5) ◽  
pp. 500-514 ◽  
Author(s):  
Robert Leeb ◽  
Claudia Keinrath ◽  
Doron Friedman ◽  
Christoph Guger ◽  
Reinhold Scherer ◽  
...  
Keyword(s):  
Communication Channel ◽  
Muscular Activity ◽  
Proof Of Concept ◽  
Closed Loop System ◽  
Head Mounted Display ◽  
Eeg Recordings ◽  
Sensorimotor Rhythms ◽  
Electroencephalogram Eeg ◽  
Healthy Participants

Healthy participants are able to move forward within a virtual environment (VE) by the imagination of foot movement. This is achieved by using a brain-computer interface (BCI) that transforms thought-modulated electroencephalogram (EEG) recordings into a control signal. A BCI establishes a communication channel between the human brain and the computer. The basic principle of the Graz-BCI is the detection and classification of motor-imagery-related EEG patterns, whereby the dynamics of sensorimotor rhythms are analyzed. A BCI is a closed-loop system and information is visually fed back to the user about the success or failure of an intended movement imagination. Feedback can be realized in different ways, from a simple moving bar graph to navigation in VEs. The goals of this work are twofold: first, to show the influence of different feedback types on the same task, and second, to demonstrate that it is possible to move through a VE (e.g., a virtual street) without any muscular activity, using only the imagination of foot movement. In the presented work, data from BCI feedback displayed on a conventional monitor are compared with data from BCI feedback in VE experiments with a head-mounted display (HMD) and in a high immersive projection environment (Cave). Results of three participants are reported to demonstrate the proof-of-concept. The data indicate that the type of feedback has an influence on the task performance, but not on the BCI classification accuracy. The participants achieved their best performances viewing feedback in the Cave. Furthermore the VE feedback provided motivation for the subjects.

Neostriatal administration of somatostatin: differential effect of small and large doses on behavior and motor control

1977 ◽  
Vol 55 (2) ◽  
pp. 234-242 ◽  
Author(s):  
M. Rezek ◽  
V. Havlicek ◽  
L. Leybin ◽  
C. Pinsky ◽  
E. A. Kroeger ◽  
...  
Keyword(s):  
Motor Control ◽  
Eye Movements ◽  
Slow Wave ◽  
Rem Sleep ◽  
Differential Effect ◽  
Slow Wave Sleep ◽  
Small Doses ◽  
Freely Moving ◽  
Behavioral Excitation ◽  
Higher Doses

The administration of small doses of somatostatin (SRIF) (0.01 and 0.1 μg) into the neostriatal complex of unrestrained, freely moving rats induced general behavioral excitation associated with a variety of stereotyped movements, tremors, and a reduction of rapid eye movements (REM) and deep slow wave sleep (SWS). In contrast, the higher doses of SRIF (1.0 and 10.0 μg) caused movements to be uncoordinated and frequently induced more severe difficulties in motor control such as contralateral hemiplegia-in-extension which restricted or completely prevented the expression of normal behavioral patterns. As a result, the animals appeared drowsy and inhibited. Analysis of the sleep-waking cycle revealed prolonged periods of a shallow SWS while REM sleep and deep SWS were markedly reduced; electroencephalogram recordings revealed periods of dissociation from behavior. The administration of endocrinologically inactive as well as the active analogues of SRIF failed to induce effects comparable with those observed after the administration of the same dose of the native hormone (10.0 μg).

Ventilatory responses to CO2 and lung inflation in tonic versus phasic REM sleep

1979 ◽  
Vol 47 (6) ◽  
pp. 1304-1310 ◽  
Author(s):  
C. E. Sullivan ◽  
E. Murphy ◽  
L. F. Kozar ◽  
E. A. Phillipson
Keyword(s):  
Eye Movements ◽  
Rem Sleep ◽  
Slow Wave Sleep ◽  
Minute Volume ◽  
Sleep State ◽  
Lung Inflation ◽  
Ventilatory Responses ◽  
Sustained Inflation ◽  
Per Se ◽  
Phasic Rem Sleep

Ventilatory responses to CO2 and to lung inflation were compared in four dogs during tonic and phasic segments of rapid-eye-movement (REM) sleep. Phasic REM sleep (P-REM) was identified by the presence of bursts of rapid eye movements, visible muscle twitchings, and frequent phasic discharges in the nuchal electromyogram. These features were absent during tonic REM sleep (T-REM). During P-REM the response of minute volume of ventilation (VI) to progressive hypercapnia (0.58 +/- 0.19 (l/min)/Torr, mean +/- SE) was significantly less than in slow-wave sleep (SWS) (1.40 +/- 0.14; P less than 0.05). In contrast, during T-REM the response (1.48 +/- 0.19) was similar to that in SWS. Similarly, during P-REM the duration of apnea (5.9 +/- 1.5 s) elicited by sustained inflation of the lungs with 1.0 liter of air, was significantly shorter than in SWS (25.8 +/- 0.8); in contrast, during T-REM the duration of apnea (17.8 +/- 3.6) was similar to that in SWS. The results indicate that previously described decreases in VI responses to CO2 and apneic responses to lung inflation during P-REM, compared to SWS, are related to the phasic phenomena of REM sleep, rather than to the REM sleep state per se.

scholarly journals EEG recording after sleep deprivation in a series of patients with juvenile myoclonic epilepsy

2005 ◽  
Vol 63 (2b) ◽  
pp. 383-388 ◽  
Author(s):  
Nise Alessandra de Carvalho Sousa ◽  
Patrícia da Silva Sousa ◽  
Eliana Garzon ◽  
Américo C. Sakamoto ◽  
Nádia I.O. Braga ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Diagnostic Delay ◽  
Quantitative Eeg ◽  
Juvenile Myoclonic Epilepsy ◽  
Myoclonic Epilepsy ◽  
Mean Delay ◽  
Epileptiform Discharges ◽  
Number Of Patients ◽  
Syndromic Diagnosis ◽  
Eeg Recordings

Seizures in Juvenile Myoclonic Epilepsy (JME) are dependent on the sleep-wake cycle and precipitant factors, among which sleep deprivation (SD) is one of the most important. Still an under diagnosed syndrome, misinterpretation of the EEGs contributes to diagnostic delay. Despite this, a quantitative EEG investigation of SD effects has not been performed. We investigated the effect of SD on EEGs in 41 patients, aged 16-50 yr. (mean 25.4), who had not yet had syndromic diagnosis after a mean delay of 8.2 yr. Two EEG recordings separated by a 48-hour interval were taken at 7 a.m. preceded by a period of 6 hours of sleep (routine EEG) and after SD (sleep-deprived EEG). The same protocol was followed and included a rest wakefulness recording, photic stimulation, hyperventilation and a post-hyperventilation period. The EEGs were analyzed as to the effect of SD on the number, duration, morphology, localization and predominance of abnormalities in the different stages. A discharge index (DI) was calculated. Out of the 41 patients, 4 presented both normal EEG recordings. In 37 (90.2%) there were epileptiform discharges (ED). The number of patients with ED ascended from 26 (70.3%) in the routine EEG to 32 (86.5%) in the sleep-deprived exam. The presence of generalized spike-wave and multispike-wave increased from 20 (54.1%) and 13 (35.1%) in the first EEG to 29 (78.4%) and 19 (51.4%) in the second, respectively (p<0.05 and p<0.01). As to localization, the number of generalized, bilateral and synchronous ED increased from 21 (56.8%) to 30 (81.1%) (p<0.01). The DI also increased; while 8 patients (21.6%) presented greater rate in the routine EEG, 25 (67.6%) did so in the sleep-deprived EEG mainly during somnolence and sleep (p<0.01). Moreover, the paroxysms were also longer in the sleep-deprived EEG. Sleep-deprived EEG is a powerful tool in JME and can contribute significantly to the syndromic characterization of this syndrome.

Artifacts

2017 ◽  
pp. 98-127
Author(s):  
Riitta Hari ◽  
Aina Puce
Keyword(s):  
Data Analysis ◽  
Eye Movements ◽  
Cardiac Activity ◽  
Signal Space Separation ◽  
Eeg Data ◽  
Eeg Recordings ◽  
Power Line Noise ◽  
Post Hoc ◽  
Space Separation ◽  
The Brain

This chapter focuses on different types of biological and nonbiological artifacts in MEG and EEG recordings, and discusses methods for their recognition and removal. Examples are given of various physiological artifacts, including eye movements, eyeblinks, saccades, muscle, and cardiac activity. Nonbiological artifacts, such as power-line noise, are also demonstrated. Some examples are given to illustrate how these unwanted signals can be identified and removed from MEG and EEG signals with methods such as independent component analysis (as applied to EEG data) and temporal signal-space separation (applied to MEG data). However, prevention of artifacts is always preferable to removing or compensating for them post hoc during data analysis. The chapter concludes with a discussion of how to ensure that signals are emanating from the brain and not from other sources.

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