scholarly journals The sleep EEG envelope: a novel, neuronal firing-based human biomarker

2021 ◽  
Author(s):  
Peter Przemyslaw Ujma ◽  
Martin Dresler ◽  
Peter Simor ◽  
Daniel Fabo ◽  
Istvan Ulbert ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
Nrem Sleep ◽  
Neuronal Firing ◽  
Sleep Eeg ◽  
Large Database ◽  
Multivariate Models ◽  
Psychological Traits ◽  
Scalp Eeg ◽  
Envelope Spectrum ◽  
Instantaneous Voltage

Sleep EEG reflects instantaneous voltage differences relative to a reference, while its spectrum reflects the degree to which it is comprised of oscillations at various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations at specific frequencies, and its spectrum reflects the rhythmicity of the occurrence of these oscillations. The ordinary sleep EEG and its spectrum have been extensively studied and its individual stability and relationship to various demographic characteristics, psychological traits and pathologies is well known. In contrast, the envelope spectrum has not been extensively studied before. In two studies, we explored the generating mechanisms and utility of studying the envelope of the sleep EEG. First, we used human invasive data from cortex-penetrating microelectrodes and subdural grids to demonstrate that the sleep EEG envelope spectrum reflects local neuronal firing. Second, we used a large database of healthy volunteers to demonstrate that the scalp EEG envelope spectrum is highly stable within individuals, especially in NREM sleep, and that it is affected by age and sex. Multivariate models based on a learning algorithm could predict both age (r=0.6) and sex (r=0.5) with considerable accuracy from the EEG envelope spectrum. With age, oscillations characteristically shifted from a 4-5 second rhythm to higher rhythms. The envelope spectrum was not associated with general cognitive ability (IQ). Our results demonstrate that the sleep envelope spectrum is a promising, neuronal firing-based biomarker of various demographic and disease-related phenotypes.

scholarly journals 0327 NREM Sleep EEG in Typically Developing and Drug-Naïve ADHD Adolescents: Data from a Longitudinal Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A124-A124
Author(s):  
T Basishvili ◽  
M Eliozishvili ◽  
T Oniani ◽  
T Tchintcharauli ◽  
I Sakhelashvili ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Nrem Sleep ◽  
Sleep Eeg ◽  
Brain Maturation ◽  
Adhd Group ◽  
Typically Developing ◽  
Eeg Activity ◽  
Theta Power ◽  
Delta Power ◽  
Drug Naïve

Abstract Introduction Structural MRI studies suggest delayed brain maturation in children with attention deficit hyperactivity disorder (ADHD). The steep adolescent decline in sleep slow wave EEG activity provides an opportunity to investigate brain electrophysiological evidence for this maturational delay. Most ADHD sleep EEG studies have been cross-sectional. Here we present data from an ongoing longitudinal study of the maturational trajectories of sleep EEG in drug-naïve ADHD and typically developing adolescents. Methods Nine children diagnosed with ADHD (combined subtype, DSM-V criteria, mean age 12.39±0.61 years), and nine typically developing controls (12.07±0.35 years) were recruited. Subjects underwent an adaptation night and all night polysomnography twice yearly at the Laboratory. Sleep EEG was analyzed using fast Fourier transform. NREM delta and theta EEG activity were compared across first two recordings. Results Group effects (ADHD vs. control) on all night delta and theta energy, and delta power were not significant (p>0.2 for all). All night theta power was lower (p=0.035) for the ADHD group, and all night NREM sleep duration trended (p=0.060) toward being lower for the ADHD group. Controlling for sleep duration differences by examining only the first 5 h of NREM sleep showed no group effect on delta power (p=0.77) and a trend toward lower theta power (p=0.057) for the ADHD group. Conclusion At age 12 to 13 years, NREM sleep delta EEG did not differ between ADHD and control subjects. Theta power, which declines at a younger age than delta, was lower in control subjects. The two recordings thus far differ only by 6 months. The entire study will provide 5 semiannual recordings and allow us to determine if the higher theta power in the ADHD group will hold and if delta power will be greater as well, and thus provide electrophysiological support for the delayed brain maturation suggested by MRI findings. Support Shota Rustaveli National Science Foundation Grant FR17_94; Subjects Recruitment Support - Mental Health Service in Tbilisi “Kamara”.

628 Longitudinal Association between NREM Sleep Depth and Arousability with ADHD and Internalizing Disorders in Adolescence

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A246-A247
Author(s):  
Anna Ricci ◽  
Julio Fernandez-Mendoza ◽  
Fan He ◽  
Susan Calhoun ◽  
Magdy Younes ◽  
...  
Keyword(s):  
Behavioral Disorders ◽  
Nrem Sleep ◽  
Internalizing Disorders ◽  
Developmental Trajectory ◽  
Sleep Eeg ◽  
Behavioral Disorder ◽  
Sleep Depth ◽  
Transition To Adolescence ◽  
Psychoactive Medications

Abstract Introduction Sleep depth decreases in the transition from childhood to adolescence, even in typically developing (TD) youth. However, it remains unknown whether this developmental trajectory in NREM sleep depth differs across adolescents with psychiatric/behavioral disorders. Methods We analyzed the sleep EEG of 392 subjects aged 5–12 at baseline and 12–22 at follow-up (45.2% female, 23.2% racial/ethnic minority), of whom 246 were TD adolescents (controls), 62 were diagnosed with a psychiatric/behavioral disorder and were taking stimulant, anti-depressant, anxiolytic, sedative and/or anti-psychotic medications, and 84 were un-medicated. NREM sleep depth was measured at both time points using the odds ratio product (ORP), which provides a standardized continuous EEG measure of NREM sleep depth/arousability (higher ORP reflects lighter NREM sleep). General linear models examined mean differences between groups on the percent change in ORP between baseline and follow-up (ΔORP) while adjusting for sex, race/ethnicity, age, BMI and AHI at follow-up, and PSG system, psychiatric/behavioral disorders, psychoactive medications and ORP at baseline as well as time-to-follow-up. Results Overall, medicated (80.4%, 95%CI=66.2–94.6) and un-medicated (66.1%, 95%CI=53.0–79.1) subjects showed a higher ΔORP compared to controls (52.2%, 95%CI=40.0–64.5, p<0.01 and p<0.05, respectively) but did not differ between each other (p=0.134). Specifically, un-medicated subjects with ADHD (n=56) showed a higher ΔORP (77.3%, 95%CI=62.4–92.1) compared to controls (p<0.01), while subjects with ADHD on stimulant medication (n=36) did not differ (66.1%, 95%CI=48.9–93.2) from controls (p=0.268) or from un-medicated ADHD subjects (p=0.303). Subjects with internalizing disorders on psychoactive medications (n=29) showed a higher ΔORP (104.9%, 95%CI=82.8–127.0) compared to controls (p<0.01) and to un-medicated subjects (n=27) with internalizing disorders (60.1%, 95%CI=36.8–83.3, p<0.01), who did not differ from controls (p=0.772). Conclusion The greater increase in ORP in the transition to adolescence in un-medicated youth with ADHD suggests that decreased NREM sleep depth may be a biomarker of the disorder. In contrast, the greater increase in ORP in medicated youth with internalizing disorders suggests that psychoactive medications impact NREM sleep depth in these children as they transition to adolescence. These data have important implications for sleep EEG studies that include medicated and un-medicated youth with comorbid psychiatric disorders. Support (if any) NIH Awards Number R01MH118308, R01HL136587, R01HL97165, R01HL63772, UL1TR000127

scholarly journals Differential modulation of NREM sleep regulation and EEG topography by chronic sleep restriction in mice

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Bowon Kim ◽  
Eunjin Hwang ◽  
Robert E. Strecker ◽  
Jee Hyun Choi ◽  
Youngsoo Kim
Keyword(s):  
Nrem Sleep ◽  
Brain Regions ◽  
Sleep Eeg ◽  
Sleep Restriction ◽  
Electrode Arrays ◽  
Sleep Regulation ◽  
Amplitude Analysis ◽  
Delta Power ◽  
Eeg Topography ◽  
Chronic Sleep

AbstractCompensatory elevation in NREM sleep EEG delta power has been typically observed following prolonged wakefulness and widely used as a sleep homeostasis indicator. However, recent evidence in human and rodent chronic sleep restriction (CSR) studies suggests that NREM delta power is not progressively increased despite of accumulated sleep loss over days. In addition, there has been little progress in understanding how sleep EEG in different brain regions responds to CSR. Using novel high-density EEG electrode arrays in the mouse model of CSR where mice underwent 18-h sleep deprivation per day for 5 consecutive days, we performed an extensive analysis of topographical NREM sleep EEG responses to the CSR condition, including period-amplitude analysis of individual slow waves. As previously reported in our analysis of REM sleep responses, we found different patterns of changes: (i) progressive decrease in NREM sleep duration and consolidation, (ii) persistent enhancement in NREM delta power especially in the frontal and parietal regions, and (iii) progressive increases in individual slow wave slope and frontal fast oscillation power. These results suggest that multiple sleep-wake regulatory systems exist in a brain region-specific manner, which can be modulated independently, especially in the CSR condition.

A machine-learning algorithm for detecting seizure termination in scalp EEG

2011 ◽  
Vol 22 ◽  
pp. S36-S43 ◽  
Author(s):  
Ali Shoeb ◽  
Alaa Kharbouch ◽  
Jacqueline Soegaard ◽  
Steven Schachter ◽  
John Guttag
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Scalp Eeg ◽  
Seizure Termination

Flunitrazepam effects on human sleep eeg spectra II: Sigma and beta alterations during NREM sleep

Life Sciences ◽  
1996 ◽  
Vol 59 (9) ◽  
pp. 117-120 ◽  
Author(s):  
Sunao Uchida ◽  
Nobuyuki Okudaira ◽  
Kyoko Nishihara ◽  
Yoshinobu Iguchi ◽  
Xin Tan
Keyword(s):  
Nrem Sleep ◽  
Sleep Eeg ◽  
Eeg Spectra ◽  
Human Sleep

Log amplitude is a linear function of log frequency in NREM sleep EEG of young and elderly normal subjects

1984 ◽  
Vol 58 (2) ◽  
pp. 158-160 ◽  
Author(s):  
I Feinberg ◽  
J.D March ◽  
T.C Floyd ◽  
G Fein ◽  
M.J Aminoff
Keyword(s):  
Linear Function ◽  
Nrem Sleep ◽  
Normal Subjects ◽  
Sleep Eeg

scholarly journals Age-related changes in slow wave activity rise time and NREM sleep EEG with and without zolpidem in healthy young and older adults

2014 ◽  
Vol 15 (9) ◽  
pp. 1037-1045 ◽  
Author(s):  
Evan D. Chinoy ◽  
Danielle J. Frey ◽  
Daniel N. Kaslovsky ◽  
Francois G. Meyer ◽  
Kenneth P. Wright
Keyword(s):  
Older Adults ◽  
Slow Wave ◽  
Rise Time ◽  
Nrem Sleep ◽  
Wave Activity ◽  
Slow Wave Activity ◽  
Sleep Eeg ◽  
Age Related ◽  
Age Related Changes

scholarly journals A new set of composite, non-redundant electroencephalogram measures of non-rapid eye movement sleep based on the power law scaling of the Fourier spectrum

2020 ◽  
Author(s):  
Róbert Bódizs ◽  
Orsolya Szalárdy ◽  
Csenge Horváth ◽  
Péter P. Ujma ◽  
Ferenc Gombos ◽  
...  
Keyword(s):  
Sex Differences ◽  
Eye Movement ◽  
Power Law ◽  
Activity Patterns ◽  
Nrem Sleep ◽  
Sleep Eeg ◽  
Spectral Peak ◽  
Sleep Spindle ◽  
Frequency Range ◽  
Electroencephalogram Eeg

AbstractA novel method for deriving composite, non-redundant measures of non-rapid eye movement (NREM) sleep electroencephalogram (EEG) is developed on the basis of the power law scaling of the Fourier spectra. Measures derived are the spectral intercept, the slope (spectral exponent), as well as the maximal whitened spectral peak amplitude and frequency in the sleep spindle range. As a proof of concept, we apply these measures on a large sleep EEG dataset (N = 175; 81 females; age range: 17–60 years) with previously demonstrated effects of age, sex and intelligence. As predicted, aging is associated with decreased overall spectral slopes (increased exponents) and whitened spectral peak amplitudes in the spindle frequency range. In addition, age associates with decreased sleep spindle spectral peak frequencies in the frontal region. Women were characterized by higher spectral intercepts and higher spectral peak frequencies in the sleep spindle range. No sex differences in whitened spectral peak amplitudes of the sleep spindle range were found. Intelligence correlated positively with whitened spectral peak amplitudes of the spindle frequency range in women, but not in men. Last, age-related increases in spectral exponents did not differ in subjects with average and high intelligence. Our findings replicate and complete previous reports in the literature, indicating that the number of variables describing NREM sleep EEG can be effectively reduced in order to overcome redundancy and Type I statistical errors in future electrophysiological studies of sleep.Author summaryGiven the tight reciprocal relationship between sleep and wakefulness, the objective description of the complex neural activity patterns characterizing human sleep is of utmost importance in understanding the several facets of brain function, like sex differences, aging and cognitive abilities. Current approaches are either exclusively based on visual impressions expressed in graded levels of sleep depth (W, N1, N2, N3, REM), whereas computerized quantitative methods provide an almost infinite number of potential metrics, suffering from significant redundancy and arbitrariness. Our current approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) are characterized by coloured noise-like properties. That is, the contribution of different frequencies to the power spectrum of the signal are best described by power law functions with negative exponents. In addition, we assume, that stages N2–N3 are further characterized by additional non-random (non-noise like, sinusoidal) activity patterns, which are emerging at specific frequencies, called sleep spindles (9–18 Hz). By relying on these assumptions we were able to effectively reduce 191 spectral measures to 4: (1) the spectral intercept reflecting the overall amplitude of the signal, (2) the spectral slope reflecting the constant ratio of low over high frequency power, (3) the frequency of the maximal sleep spindle activity and (4) the amplitude of the sleep spindle spectral peak. These 4 measures were efficient in characterizing known age-effects, sex-differences and cognitive correlates of sleep EEG. Future clinical and basic studies are supposed to be significantly empowered by the efficient data reduction provided by our approach.

scholarly journals Sleep spindles, ripples, and interictal epileptiform discharges in the human anterior and mediodorsal thalamus

2021 ◽  
Author(s):  
Orsolya Szalardy ◽  
Peter Simor ◽  
Peter Przemyslaw Ujma ◽  
Zsofia Jordan ◽  
Laszlo Halasz ◽  
...  
Keyword(s):  
Neural Plasticity ◽  
Nrem Sleep ◽  
Cortical Activity ◽  
Sleep Spindles ◽  
Time Frequency ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Human Thalamus ◽  
Result Show

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons, the inhibition of which is caused by the NREM-dependent activation of GABAergic neurons in the reticular thalamic nucleus. Reports suggest a link between sleep spindles and several forms of interictal epileptic discharges (IEDs) which are considered as expressions of pathological off-line neural plasticity in the central nervous system. Here we investigated the relationship between thalamic sleep spindles, IEDs and ripples in the anterior and mediodorsal nuclei (ANT and MD) of epilepsy patients. Whole-night LFP from the ANT and MD were co-registered with scalp EEG/polysomnography by using externalized leads in 15 epilepsy patients undergoing Deep Brain Stimulation protocol. Slow (~12 Hz) and fast (~14 Hz) sleep spindles were present in the human ANT and MD. Roughly, one third of thalamic sleep spindles were associated with IEDs or ripples. Both IED- and ripple-associated spindles were longer than pure spindles. IED-associated thalamic sleep spindles were characterized by broadband increase in thalamic and cortical activity, both below and above the spindle frequency range, whereas ripple-associated thalamic spindles exceeded pure spindles in terms of 80-200 Hz thalamic, but not cortical activity as indicated by time-frequency analysis. These result show that thalamic spindles coupled with IEDs are reflected at the scalp slow and beta-gamma oscillation as well. IED density during sleep spindles in the MD, but not in the ANT was identified as correlates of years spent with epilepsy, whereas no signs of pathological processes were correlated with measures of ripple and spindle association. Furthermore, the density of ripple-associated sleep spindles in the ANT showed a positive correlation with general intelligence. Our findings indicate the complex and multifaceted role of the human thalamus in sleep spindle-related physiological and pathological neural plasticity.

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