Repeated characterization, analysis of variance limitation and discrimination analysis classification of EEG-activity patterns in human sleep]

1. To describe quantitatively and to deliminate nine EEG sleep patterns, mean values and standard deviations of abundances of the frequencies 0.8 ... 1.8 c/sec, 2...3.5 c/sec, 4...13c/sec, 14 to 17 c/sec, 18 to 22 c/sec, and 23 to 40 c/sec as well as of the average amplitudes in selected frequency ranges were calaculated and the distributions represented. 2. All nine EEG activity patterns could be separated by means of univariate and multivariate analyses of variance on the basis of all 28 as well as the 17 indispensable variables. 3. In the course of a stepwise reduction of variables within the framework of a linear discriminant analysis an optimal set of 17 variables was determined for the separation of the patterns, comprising: the percent quantity of the frequencies 0.8 ... 3.5 c/sec, 7 ... 9 c/sec and 18 to 40 c/sec as well as the average amplitudes in the frequency ranges 0.8 to 3.5 c/sec and 7.5 to 40 c/sec. 4. By linear regression analyses it could be shown that the sleep scording system used, can be reflected on an interval scale with the aid of discriminant functions; this can be achieved on the basis of the optimal set of variables as well as of the five most indispensable variables. 5. Finally the degree of the objectivity of the scoring procedures was demonstrated. Advantages and disadvantages of sleep scoring systems were discussed and possibilities of the utilization of results suggested, also in respect to the further development of the automatic recognition of EEG activity patterns.     

Variance and discriminatory analyses for the classification of wakefulness-dependent EEG patterns]

1. To describe 8 alertness-dependent EEG activity patterns to be observed during wakefulness with eyes closed, mean values and standard deviations of the frequencies 4, ..., 13, 14 to 17, 18 to 22 and 23 to 40 c/sec, of the percentage activity in the theta, alpha and beta bands as well as of the theta and alpha amplitudes were calculated. 2. On the basis of 18 variables significant differences between 7 activity patterns were ascertained by means of univariate and multivariate analyses of variance. 3. In the course of stepwise reduction of variables within the framework of a linear discriminatory analysis, an optimal set of variables was determined for the separation of the patterns comprising the following variables: mean value and standard deviation of the alpha amplitudes and mean value of the theta amplitudes as well as the percent quantity of the frequencies 3, ..., 7, 10, 14 to 17 and 23 to 40 c/sec. 4. By means of a linear regression analysis it was shown that the EEG scoring system can be reflected on an interval scale. In connection with results on the reliability of the methods used the results were discussed.     

Selection of valid and reliable EEG features for predicting auditory and visual alertness levels

A selection procedure with three rules, high efficiency, low individual variability, and low redundancy, was developed to screen electroencephalogram (EEG) features for predicting behavioral alertness levels. A total of 24 EEG features were derived from temporal, frequency spectral, and statistical analyses. Behavioral alertness levels were quantified by correct rates of performance on an auditory and a visual vigilance task, separately. In the auditory task study, a subset of three EEG features, the relative spectral amplitudes in the alpha (alpha%, 8-13 Hz) and theta (theta%, 4-8 Hz) bands, and the mean frequency of the EEG spectrum (MF), was found to be the best combination for predicting the auditory alertness level. In the visual task study, the mean frequency of the beta band (Fbeta, 13-32 Hz) was the only EEG feature selected. The application of an averaging subwindow procedure within a moving time window to EEG analysis increased the predictive power of EEG features and decreased the disturbing effect of movement artifacts on the EEG data.     

EEG source identification: frequency analysis during sleep

This article deals with a new approach in sleep characterization that combines EEG source localisation methods with standard frequency analysis of multielectrode EEGs. First, we describe the theoretical methodology and the benefits that we get from a three-dimensional image (LORETA) of the cerebral activity related to a frequency band. Then, this new application is used as signal-processing technique on sleep EEG recordings obtained from young male adults using four frequency bands (delta 0.5-3.5 Hz, theta 4.0-7.5 Hz, alpha 8.0-12.5 Hz and beta 13.0-32.0 Hz) in different sleep stages. Finally, we show that the obtained results are highly consistent with other physiological assessments (standard EEG mapping, functional magnetic resonance imaging, etc.), but give us more realistic additional information on the generators of electromagnetic cerebral activity.     

Analysis and modeling of time-variant amplitude–frequency couplings of and between oscillations of EEG bursts

Low-frequency (0.5-2.5 Hz) and individually defined high-frequency (7-11 or 8-12 Hz; 11-15 or 14-18 Hz) oscillatory components of the electroencephalogram (EEG) burst activity derived from thiopental-induced burst-suppression patterns (BSP) were investigated in seven sedated patients (17-26 years old) with severe head injury. The predominant high-frequency burst oscillations (>7 Hz) were detected for each patient by means of time-variant amplitude spectrum analysis. Thereafter, the instantaneous envelope (IE) and the instantaneous frequency (IF) were computed for these low- and high-frequency bands to quantify amplitude-frequency dependencies (envelope-envelope, envelope-frequency, and frequency-frequency correlations). Time-variant phase-locking, phase synchronization, and quadratic phase couplings are associated with the observed amplitude-frequency characteristics. Additionally, these time-variant analyses were carried out for modeled burst patterns. Coupled Duffing oscillators were adapted to each EEG burst and by means of these models data-based burst simulations were generated. Results are: (1) strong envelope-envelope correlations (IE courses) can be demonstrated; (2) it can be shown that a rise of the IE is associated with an increase of the IF (only for the frequency bands 0.5-2.5 and 7-11 or 8-12 Hz); (3) the rise characteristics of all individually averaged envelope-frequency courses (IE-IF) are strongly correlated; (4) for the 7-11 or 8-12 Hz oscillation these associations are weaker and the variation between the time courses of the patients is higher; (5) for both frequency ranges a quantitative amplitude-frequency dependency can be shown because higher IE peak maxima are accompanied by stronger IF changes; (6) the time range of significant phase-locking within the 7-11 or 8-12 Hz frequency bands and of the strongest quadratic phase couplings (between 0.5-2.5 and 7-11 or 8-12 Hz) is between 0 and 1,000 ms; (7) all phase coupling characteristics of the modeled bursts accord well with the corresponding characteristics of the measured EEG burst data. All amplitude-frequency dependencies and phase locking/coupling properties described here are known from and can be discussed using coupled Duffing oscillators which are characterized by autoresonance properties.     

Principal component analysis of electroencephalographic activity during sleep and wakefulness in the spider monkey (Ateles geoffroyi)

The study of electroencephalographic (EEG) activity during sleep in the spider monkey has provided new insights into primitive arboreal sleep physiology and behavior in anthropoids. Nevertheless, studies conducted to date have maintained the frequency ranges of the EEG bands commonly used with humans. The aim of the present work was to determine the EEG broad bands that characterize sleep and wakefulness in the spider monkey using principal component analysis (PCA). The EEG activity was recorded from the occipital, central, and frontal EEG derivations of six young-adult male spider monkeys housed in a laboratory setting. To determine which frequencies covaried and which were orthogonally independent during sleep and wakefulness, the power EEG spectra and interhemispheric and intrahemispheric EEG correlations from 1 to 30 Hz were subjected to PCA. Findings show that the EEG bands detection differed from those reported previously in both spider monkeys and humans, and that the 1–3 and 2–13 Hz frequency ranges concur with the oscillatory activity elucidated by cellular recordings of subcortical regions. Results show that applying PCA to the EEG spectrum during sleep and wakefulness in the spider monkey led to the identification of frequencies that covaried with, and were orthogonally independent of, other frequencies in each behavioral vigilance state. The new EEG bands differ from those used previously with both spider monkeys and humans. The 1–3 and 2–13 Hz frequency ranges are in accordance with the oscillatory activity elucidated by cellular recordings of subcortical regions in other mammals.     

Regional features of the electrical activity of the neocortex in the dog over a wide range of frequencies

Autospectral characteristics (ASC) of potentials of different neocortical areas of dogs in a state of quiet wakefulness were studied in a wide frequency band (1-100 Hz) by means of correlation-spectral analysis. A transition from evaluation of the mean power tendencies to a construction of distributions of different power levels for each of five arbitrarily chosen frequency bands permitted to reveal regional differences in ASC of each animal as well as interindividual EEG distinctions. The regional differences observed in all frequency bands (though not equally expressed) including the higher ones indicate not only the informativity of high-frequency components of electrical neocortical activity but also their neuronal origin.     

Common genetic origins for EEG, alcoholism and anxiety: the role of CRH-BP

The resting EEG is a dynamic index of cortical activation, cognitive function and consciousness and is therefore an intermediate phenotype for many behaviors in which arousal is implicated such as anxiety and alcoholism. We performed a dense whole genome linkage scan using 3878 unlinked SNPs in a large pedigree derived from a population isolate sample of 328 Plains American Indians. Alpha (8-13 Hz), theta (4-8 Hz) and beta (13-30 Hz) EEG power was heritable (0.58-0.27) and stable over a 2 year period (r = 0.82-0.53). Genetic correlations between frequency bands were high (0.75). Linkage peaks for EEG power in all three frequency bands converged on chromosome 5q13-14 with genome-wide significant LOD scores of 3.5 (empirical p<0.0001) for alpha and beta power. A logical candidate gene, corticotropin releasing hormone-binding protein (CRH-BP), was located at the apex of these convergent linkage peaks. CRH-BP was significantly associated with alpha power in the Plains Indians and also in a replication sample of 188 Caucasians. Moreover, the same SNPs and haplotypes, located within the CRH-BP haplotype block, were also associated with anxiety disorders in the Plains Indians and alcohol use disorders in the Caucasians. CRH-BP modulates CRH which influences cortical and hippocampal EEG activity and is the primary mediator of the neuroendocrine stress response. Our results suggest a likely role for CRH-BP in stress-related alcoholism and highlight the use of the resting EEG as an intermediate phenotype for arousal-related behaviors such as anxiety and addiction.     

Relationship between cortical electrical and cardiac autonomic activities in the awake lizard, Gallotia galloti

ECG and EEG signals were simultaneously recorded in lizards, Gallotia galloti, both in control conditions and under autonomic nervous system (ANS) blockade, in order to evaluate possible relationships between the ANS control of heart rate and the integrated central nervous system activity in reptiles. The ANS blockers used were prazosin, propranolol, and atropine. Time-domain summary statistics were derived from the series of consecutive R-R intervals (RRI) of the ECG to measure beat-to-beat heart rate variability (HRV), and spectral analysis techniques were applied to the EEG activity to assess its frequency content. Both prazosin and atropine did not alter the power spectral density (PSD) of the EEG low frequency (LF: 0.5-7.5 Hz) and high frequency (HF: 7.6-30 Hz) bands, whereas propranolol decreased the PSD in these bands. These findings suggest that central beta-adrenergic receptor mechanisms could mediate the reptilian waking EEG activity without taking part any alpha(1)-adrenergic and/or cholinergic receptor systems. In 55% of the lizards in control conditions, and in approximately 43% of the lizards under prazosin and atropine, a negative correlation between the coefficient of variation of the series of RRI value (CV(RRI)) and the mean power frequency (MPF) of the EEG spectra was found, but not under propranolol. Consequently, the lizards' HRV-EEG-activity relationship appears to be independent of alpha(1)-adrenergic and cholinergic receptor systems and mediated by beta-adrenergic receptor mechanisms.     

Test of statistical stability of the electroencephalogram

The stability of the EEG during eyes closed and eyes open were tested by the statistical method. The EEG records of 25 s were segmented into ten 2.5 s intervals for each state. The mean and variance and power spectra (2.5 to 17.5 Hz at resolution of 2.5 Hz) were calculated for each segment of 2.5 s interval. Thus, the sequences of mean values, variances and power at each frequency component were obtained for 25 s epoch. The stationarity of these sequences were tested by the run test and the trend test. The stationarity of mean, variance and power spectra were not rejected for 25 s records by any of two tests. In the records of 50 s, about 10–20% of records tested were rejected. The nonstationarity of the EEG appeared for 50 s records. This means that the EEG during period the eyes were closed, or opened can be regarded as stationary over time period as long as at least 25 s.     

Localizing Movement-Related Primary Sensorimotor Cortices with Multi-Band EEG Frequency Changes and Functional MRI

Electroencephalographic (EEG) oscillations in multiple frequency bands can be observed during functional activity of the cerebral cortex. An important question is whether activity of focal areas of cortex, such as during finger movements, is tracked by focal oscillatory EEG changes. Although a number of studies have compared EEG changes to functional MRI hemodynamic responses, we can find no previous research that relates the fMRI hemodynamic activity to localization of the multiple EEG frequency changes observed in motor tasks. In the present study, five participants performed similar thumb and finger movement tasks in parallel EEG and functional MRI studies. We examined changes in five frequency bands (from 5–120 Hz) and localized them using 256 dense-array EEG (dEEG) recordings and high-resolution individual head models. These localizations were compared with fMRI localizations in the same participants. Results showed that beta-band (14–30 Hz) desynchronizations (power decreases) were the most robust effects, appearing in all individuals, consistently localized to the hand region of the primary motor cortex, and consistently aligned with fMRI localizations.     

The effects of morphine on the relationship between fetal EEG, breathing and blood pressure signals using fast wavelet transform

In this study, we introduce the fast wavelet transform (WT) as a method for investigating the effects of morphine on the electroencephalogram (EEG), respiratory activity and blood pressure in fetal lambs. Morphine was infused intravenously at 25 mg/h. The EEG, respiratory activity and blood pressure signals were analyzed using WT. We performed wavelet decomposition for five sets of parameters D _2j where -1 < j 5. The five series WTs represent the detail signal bandwidths: 1, 16–32 Hz; 2, 8–16 Hz; 3, 4–8 Hz; 4, 2–4 Hz; 5, 1–2 Hz. Before injection of the high-dose morphine, power in the EEG was high in all six frequency bandwidths. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the low-voltage fast activity (LVFA) EEG signal. Respiratory activity was observed during only some of the LVFA periods, and was completely absent during high-voltage slow activity (HVSA) EEG. The respiratory signal showed dominant power in the fourth wavelet band, and less power in the third and fifth bands. The blood pressure signal was also characterized by dominant power in the fourth wavelet band. This power was significantly increased during periods of respiratory activity. There was a strong relationship between fetal EEG, blood pressure and breathing movements. However, the injection of high-dose morphine resulted in a disruption of the normal cyclic pattern between the two EEG states and a significant increase in power in the first wavelet band. In addition, the high-dose drug resulted in a significant increase in the power of respiratory signal in the fourth and fifth wavelet bands, while power was reduced in the third wavelet band. Breathing activity was also continuous after the drug. The high-dose morphine also caused a temporary power shift from the third wavelet band to the fourth wavelet band for the 30-min period after injection of drug. Finally, high-dose morphine completely destroyed the correlation between EEG, breathing and blood pressure signals.     

Human gamma oscillations during slow wave sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.     

Electroencephalographic characteristic of cognitive-specific alerting attention in verbal learning--III: Localized characteristics of EEG spatial synchronization

Electroencephalograms (EEG) were recorder in 19 standard derivations in 88 healthy subjects, while they were in the states: rest with eyes open; memorization (learning) of verbal bilingual semantic pairs (Latin and Russian languages); the retrieval of the rote information from memory (control). We compared estimates of EEG coherence in these states for the frequency bands theta (4-7 Hz), alpha-1 (7-10 Hz), alpha-2 (10-13 Hz), beta-1 (13-18 Hz), beta-2 (18-30 Hz), gamma (30-40 Hz). When compared with the rest most strongly expressed: for memorization a decrease of coherence in the pairs of derivations from frontal and central areas of the cortex in the EEG frequency bands; for retrieval an increase of coherence in interhemispheric derivation pairs of pariental-occipital region in majority of the frequency bands. For the retrieval also increases of coherence in the beta2 and gamma bands, along with coherence decreases at low frequencies take place in pairs formed by derivations from the parieto-occipital region with derivations from the frontal and the central ones. Dynamics of EEG coherence in comparisons of memorization and retrieval from the rest and each are expressed significantly more in the interhemispheric and crosshemispheric pairs of derivations than in the intrahemispheric pairs. Revealed topographic specificity of the dynamics of EEG coherence by changing the states is considered in terms of ideas about cognitive-specific forms of sustained goal-directed mental attention.     

Analysis of EEG characteristic at early stages of depression using method of independent components

Independent Component Analysis (ICA) was used for 19-channel resting EEG analysis 111 patients at early stages of depressive disorder and 526 age-matched healthy subjects. Comparison of independent components power spectra in depressed patients and healthy subjects in two states: Eyes closed and Eyes open, has revealed significant differences between groups for three frequency bands: Theta (4-7.5 Hz), Alpha (7.5-14 Hz), and Beta (14-20 Hz). Increased power of alpha and theta activity in depressed patients at parietal and occipital sites may be caused by decreased cortical activation of these regions. Diffuse enhancement of beta activity level can correlate with anxiety symptoms which take an important place in clinical picture of depressive disorder at early stages. Using of ICA method for comparison of spectral characteristics of EEG in groups of patients with different brain pathology and healthy subjects gives a possibility to localize more precisely the discovered differences as compare to traditional analysis of EEG spectra.     

The impact of experimental instruction on changes in EEG power during verbal creative thinking in men and women

Features of EEG pattern during verbal creative thinking depending on experimental instruction were studied in men and women. Spectral power density was analyzed in six frequency bands (4-30 Hz). Performance of a creative task produced an increase in the power of theta (4-6 Hz) and beta2 (20-40 Hz) components and decrease in the power of alpha (8-13 Hz) and betal (13-20 Hz). Changes in the alpha and betal bands were observed, predominantly, in the posterior areas, whereas power of the thetal and beta2 bands increased in the anterior areas. Independently of instruction, women demonstrated greater synchronization in the theta1 band than men, whereas in men the desynchronization in the alpha2 band (10-13 Hz) was more pronounced. When the subjects were instructed to create original sentences, a widespread decrease in the EEG power was observed in the band of 8-30 Hz as compared to instruction "to create sentences". Thus, the instruction-related changes in EEG power were not gender-specific. They may reflect neural activity mediating selective attention.     

Heart-rate variability in children. Spectral analysis of developmental changes between 5 and 24 years

The variation in instantaneous heart rate is most prominent in infants and younger subjects. In a preliminary study of the effects of maturation on heart rate, we compared the heart rate variations of 29 children and young adults in three groups between 5 and 24 years of age. We used spectral analysis to determine the intensity of the variations in each of the two main frequency bands in which variations occur: HF, 0.15-0.45 Hz, and LF, 0.03-0.15 Hz. Three-minute segments of continuous instantaneous heart rate were recorded for each subject in standing and supine positions. The group mean LF and HF amplitudes and the L/H ratio decreased between 5 and 10 years of age in both positions, significantly for LF and L/H in the supine position (p less than 0.05). Half of the youngest group of children had adult LF amplitude values by 5 years of age; the others had much higher levels, indicating increased low frequency variation at this age. Thus the high variation in heart rate in very young subjects is most prominent in the LF range. These preliminary results, considered with previous pharmacological studies, suggest that many children have a significant decrease in sympathetic activity between 5 and 10 years of age and possibly a slight decrease in parasympathetic activity. Spectral analysis of heart rate appears a promising technique for investigating the development of neural control of the heart.     

Electroencephalographic changes in the lateral septum complex following systemic administration of DES-TYR1 -α-endorphin,Des-Tyr1-γ-endorphin and haloperidol in rats

The influence of systemically administered Des-Tyr¹-α-endorphin (DTαE), Des-Tyr¹-γ-endorphin (DTγE) and haloperidol on electroencephalographic (EEG) activity of the lateral septum complex (LSC) and the frontal cortex was studied in male rats. DTαE (2 μg) significantly increased whereas DTγE (10 μg) significantly decreased the amounts of activity in the 5 Hz band. In addition, DTαE promoted production of 15 - 20 Hz activity, while DTγE decreased the amount of 20 - 30 Hz activity. EEG activity exhibited a marked variability which persisted throughout the recording session following administration of the peptides. Haloperidol markedly decreased the proportion of 10 - 15 Hz activity. The alterations in EEG of the frontal cortex were similar to those in LSC but less pronounced. The differences in the time course and frequency bands affected suggest that the effects of peptides and haloperidol on EEG activity of LSC are not mediated by the same mechanisms.     

Quantitative Changes in the Sleep EEG at Moderate Altitude (1630 m and 2590 m)

Background

Previous studies have observed an altitude-dependent increase in central apneas and a shift towards lighter sleep at altitudes >4000 m. Whether altitude-dependent changes in the sleep EEG are also prevalent at moderate altitudes of 1600 m and 2600 m remains largely unknown. Furthermore, the relationship between sleep EEG variables and central apneas and oxygen saturation are of great interest to understand the impact of hypoxia at moderate altitude on sleep.

Methods

Fourty-four healthy men (mean age 25.0±5.5 years) underwent polysomnographic recordings during a baseline night at 490 m and four consecutive nights at 1630 m and 2590 m (two nights each) in a randomized cross-over design.

Results

Comparison of sleep EEG power density spectra of frontal (F3A2) and central (C3A2) derivations at altitudes compared to baseline revealed that slow-wave activity (SWA, 0.8–4.6 Hz) in non-REM sleep was reduced in an altitude-dependent manner (∼4% at 1630 m and 15% at 2590 m), while theta activity (4.6–8 Hz) was reduced only at the highest altitude (10% at 2590 m). In addition, spindle peak height and frequency showed a modest increase in the second night at 2590 m. SWA and theta activity were also reduced in REM sleep. Correlations between spectral power and central apnea/hypopnea index (AHI), oxygen desaturation index (ODI), and oxygen saturation revealed that distinct frequency bands were correlated with oxygen saturation (6.4–8 Hz and 13–14.4 Hz) and breathing variables (AHI, ODI; 0.8–4.6 Hz).

Conclusions

The correlation between SWA and AHI/ODI suggests that respiratory disturbances contribute to the reduction in SWA at altitude. Since SWA is a marker of sleep homeostasis, this might be indicative of an inability to efficiently dissipate sleep pressure.     

Energy analysis reveals the negative effect of delays in passive movement mirror therapy

Wavelet transform energy analyses of the mean and standard error of the electromyogram (EMG) and electroencephalogram (EEG) of eight subjects were investigated in passive movement mirror therapies with no delay (in-phase) and with delay (out-of-phase) situations in two frequency bands of 7.81–15.62 and 15.62–31.25?Hz. It was found that the energy levels of EEG at electrode C4 in the in-phase situation were lower than those in out-of-phase situations, while the energy levels of flexor and extensor forearm muscle groups were larger. With two exceptions, this pattern could be seen in all other subjects. The difference between the in-phase (D0) and out-of-phase situations (D025 and D05) for the frequency range of 15.62–31.25?Hz was found to be significant at a significance level of 0.05 (paired t-test analysis). The respective elevation and decline of EEG and EGM with regard to the increase of the delay may indicate the necessity for synchronization of passive movement and mirror therapy.