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.     

Amplitude-frequency modulation of electroencephalogram associated with rhythmic movements

Evoked, motor and final potentials and some other EEG phenomena are suggested as additional components accompanying movements, external stimuli, imagination etc. Obviously, the EEG reactions are not restricted to them. On the basis of the method of synchronic averaging a way for detecting the amplitude-frequency modulation (AFM) related to the repeated movements is proposed. This method permitted to reliably single out the EEG effects which sometimes were detected by visual analysis. As the experiments showed the depth of AFM EEG accompanying the movements was about 3-6% (in this case spontaneous AFM plays the role of noise and equals 50% or more). Relations between changes in AFM for EEG recorded from various points, as well as for EEG rhythms were investigated.     

Kinematic variability in running: a caution regarding use of the spanning set measure

The spanning set technique quantifies intertrial variability as the span between polynomial curves representing upper and lower standard deviation curves of a repeated movement. This study aimed to assess the validity of the spanning set technique in quantifying variability and specifically to determine its sensitivity to variability presented at different phases of a movement cycle. Knee angle data were recorded from a male participant completing 12 overground running trials. Variability was added to each running trial at five different phases of the running stride. Ten variability magnitudes were also used to assess the effect of variability magnitude on the spanning set measure. Variability was quantified in all trials using mean deviation and the spanning set measure. Results of a repeated-measures ANOVA showed significant differences between the spanning set score for trials using different phases of added variability. In contrast, mean deviation values showed no difference related to the phase of added variability. Therefore, the spanning set technique cannot be recommended as a valid measure of intertrial movement variability.     

Time-Dependent Statistical and Correlation Properties of Neural Signals during Handwriting

To elucidate the cortical control of handwriting, we examined time-dependent statistical and correlational properties of simultaneously recorded 64-channel electroencephalograms (EEGs) and electromyograms (EMGs) of intrinsic hand muscles. We introduced a statistical method, which offered advantages compared to conventional coherence methods. In contrast to coherence methods, which operate in the frequency domain, our method enabled us to study the functional association between different neural regions in the time domain. In our experiments, subjects performed about 400 stereotypical trials during which they wrote a single character. These trials provided time-dependent EMG and EEG data capturing different handwriting epochs. The set of trials was treated as a statistical ensemble, and time-dependent correlation functions between neural signals were computed by averaging over that ensemble. We found that trial-to-trial variability of both the EMGs and EEGs was well described by a log-normal distribution with time-dependent parameters, which was clearly distinguished from the normal (Gaussian) distribution. We found strong and long-lasting EMG/EMG correlations, whereas EEG/EEG correlations, which were also quite strong, were short-lived with a characteristic correlation durations on the order of 100 ms or less. Our computations of correlation functions were restricted to the spectral range (13–30 Hz) of EEG signals where we found the strongest effects related to handwriting. Although, all subjects involved in our experiments were right-hand writers, we observed a clear symmetry between left and right motor areas: inter-channel correlations were strong if both channels were located over the left or right hemispheres, and 2–3 times weaker if the EEG channels were located over different hemispheres. Although we observed synchronized changes in the mean energies of EEG and EMG signals, we found that EEG/EMG correlations were much weaker than EEG/EEG and EMG/EMG correlations. The absence of strong correlations between EMG and EEG signals indicates that (i) a large fraction of the EEG signal includes electrical activity unrelated to low-level motor variability; (ii) neural processing of cortically-derived signals by spinal circuitry may reduce the correlation between EEG and EMG signals.     

Long photoperiod restores the 24-h rhythm of sleep and EEG slow-wave activity in the Djungarian hamster (Phodopus sungorus)

Photoperiod influences the distribution of sleep and waking and electroencephalogram (EEG) power density in the Djungarian hamster. In an experimental procedure combining short photoperiod (SP) and low ambient temperature, the light-dark difference in the amount of sleep was decreased, and the changes in slow-wave activity (SWA) (mean EEG power density between 0.75 and 4.0 Hz) in nonrapid eye movement (NREM) sleep within 24 h were abolished. These findings, obtained in three different groups of animals, suggested that at the lower ambient temperature, the influence of the circadian clock on sleep-wake behavior was diminished. However, it remained unclear whether the changes were due to the photoperiod, ambient temperature, or both. Here, the authors show that EEG and electromyogram recordings in a single group of animals sequentially adapted to a short and long photoperiod (LP) at low ambient temperature (approximately 15 degrees C) confirm that EEG power is reduced in SP. Moreover, the nocturnal sleep-wake behavior and the changes in SWA in NREM sleep over 24 h were restored by returning the animals to LP and retaining ambient temperature at 15 degrees C. Therefore, the effects cannot be attributed to ambient temperature alone but are due to a combined effect of temperature and photoperiod. When the Djungarian hamster adapts to winter conditions, it appears to uncouple sleep regulation from the circadian clock.     

Quantitative assessment of maps of the cortical background potentials during the adaptation of freely moving animals to environmental situations

Utilization of spectral-correlation methods of EEG analysis, due to necessary averaging in time, does not make it possible to detect dynamic phenomena in spatial-temporal organization of brain potentials. Non-traditional method is presented of quantitative evaluation of the changes of spatial-temporal correlation of cortical potentials--comparison of successive momentary potentials relief (electroencephalotopograms--EETG). Joint utilization of dynamics of similarity coefficients of successive EETG (Ket), mean values of EETG (Yet) and some other parameters allows to judge about dynamic properties of spatial correlations of potentials of freely moving animals in adaptation process to the environment during which alternation is established of the active and passive phases in decaminute intervals. Quantitative evaluation of spatial-temporal organization of the parameters of rabbits cortical potentials in these phases and in transition periods has revealed their informative possibilities.     

Effects of exponential compression curves with nitrogen injection in humans

Two series of experiments were carried out on humans to study the effects of fast and slow exponential compression curves with N2 additions. Eight subjects in the first series and 13 subjects in the second series were analyzed up to the depths of 400-450 m of seawater (msw). The data indicated that injections of N2 in He-O2 mixture reduced or suppressed the hyperbaric tremor in the two series. Electroencephalographic (EEG) changes were recorded with the two types of compression, but these changes (increase in slow waves, decrease in alpha-activity, appearance of microsleep EEG traces) were more important with the fast exponential compression curves between 200 and 300 msw than with the slow exponential curves. The effects of the fast rates of compression on EEG activities were not compensated by addition of 4-5% N2. Consequently, the fast exponential compression curves, even with N2 injections, cannot be used without risk and must be avoided; the slow exponential compression curve with N2 injection allowed a human subject to reach 450 msw in satisfactory condition, i.e., without tremor and with light EEG changes.     

Improving N1 classification by grouping EEG trials with phases of pre-stimulus EEG oscillations

A reactive brain-computer interface using electroencephalography (EEG) relies on the classification of evoked ERP responses. As the trial-to-trial variation is evitable in EEG signals, it is a challenge to capture the consistent classification features distribution. Clustering EEG trials with similar features and utilizing a specific classifier adjusted to each cluster can improve EEG classification. In this paper, instead of measuring the similarity of ERP features, the brain states during image stimuli presentation that evoked N1 responses were used to group EEG trials. The correlation between momentary phases of pre-stimulus EEG oscillations and N1 amplitudes was analyzed. The results demonstrated that the phases of time–frequency points about 5.3 Hz and 0.3 s before the stimulus onset have significant effect on the ERP classification accuracy. Our findings revealed that N1 components in ERP fluctuated with momentary phases of EEG. We also further studied the influence of pre-stimulus momentary phases on classification of N1 features. Results showed that linear classifiers demonstrated outstanding classification performance when training and testing trials have close momentary phases. Therefore, this gave us a new direction to improve EEG classification by grouping EEG trials with similar pre-stimulus phases and using each to train unit classifiers respectively.     

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.     

Towards a novel monitor of intraoperative awareness: selecting paradigm settings for a movement-based brain-computer interface

During 0.1-0.2% of operations with general anesthesia, patients become aware during surgery. Unfortunately, pharmacologically paralyzed patients cannot seek attention by moving. Their attempted movements may however induce detectable EEG changes over the motor cortex. Here, methods from the area of movement-based brain-computer interfacing are proposed as a novel direction in anesthesia monitoring. Optimal settings for development of such a paradigm are studied to allow for a clinically feasible system. A classifier was trained on recorded EEG data of ten healthy non-anesthetized participants executing 3-second movement tasks. Extensive analysis was performed on this data to obtain an optimal EEG channel set and optimal features for use in a movement detection paradigm. EEG during movement could be distinguished from EEG during non-movement with very high accuracy. After a short calibration session, an average classification rate of 92% was obtained using nine EEG channels over the motor cortex, combined movement and post-movement signals, a frequency resolution of 4 Hz and a frequency range of 8-24 Hz. Using Monte Carlo simulation and a simple decision making paradigm, this translated into a probability of 99% of true positive movement detection within the first two and a half minutes after movement onset. A very low mean false positive rate of <0.01% was obtained. The current results corroborate the feasibility of detecting movement-related EEG signals, bearing in mind the clinical demands for use during surgery. Based on these results further clinical testing can be initiated.     

Principles of the organization of intestinal epithelium and its recovery from damage revealed by modeling

Using the developed method of modelling the curves of the fraction of labelled indexes (FLI) in the small intestine epithelium, a relationship was found between the FLI shape and duration of the S phase and the whole generation cycle for various generations of proliferating crypt cells. On the basis of the comparison between the theoretical and experimental FLI the normal values of the generation cycles along the crypt were specified for various intestinal parts. FLI were shaped along the crypt at various time intervals after irradiation. As a result, the data were obtained on the correlation between the duration of generation cycles and their phases during the postirradiation period and for various cell generations.     

Perceived exertion is associated with an altered brain activity during exercise with progressive hyperthermia.

The present study tested the hypothesis that perceived exertion during prolonged exercise in hot environments is associated with changes in cerebral electrical activity rather than changes in the electromyogram (EMG) of the exercising muscles. Therefore, electroencephalogram (EEG) in three positions (frontal, central, and occipital cortex), EMG, rating of perceived exertion (RPE), and core temperature were measured in 14 subjects during submaximal exercise in normal (18 degrees C, control) and hot (40 degrees C, hyperthermia) environments. RPE increased from 11 +/- 1 units at 5 min to 20 +/- 0 units at exhaustion (50 +/- 3 min) in the trial with progressive hyperthermia, whereas exercise in the control trial was maintained with a stable core temperature for 1 h without exhausting the subjects. Altered EEG activity was observed in all electrode positions, and stepwise forward-regression analysis identified core temperature and a frequency index of the EEG over the frontal cortex as the best predictors of RPE. In contrast, there were no significant correlations between RPE and any of the measured EMG parameters (median spectral frequency, root mean square, or amplitude), and the EMG parameters were not different in hyperthermia compared with control. Thus hyperthermia does not seem to affect the activation pattern of the muscles. Rather, the linear correlation among core temperature, EEG frequency index, and RPE indicates that alterations in cerebral activity may be associated with the hyperthermia-induced development of fatigue during prolonged exercise in hot environments.     

Amplitude modulation of an electroencephalogram, connected with initiation and cessation of movement

Amplitude modulations of electroencephalogram were studied under the condition of single voluntary movements of different duration, their mental reproduction and unvoluntary movements (T-reflex). Specific patterns of the averaging integrated electroencephalogram (waves P1, N1, P2) were detected under initiation or termination of the voluntary movements and their mental reproduction. EEG amplitude modulations were analysed with the accompanying movement of different duration. The experiments showed interferation waves P1, N1, P2 under brief movements. These specific patterns of EEG could be represented by the efferent and afferent components of the central motor programs.     

Analysis of diaphragm movement during tidal breathing and during its activation while breath holding using MRI synchronized with spirometry

Using magnetic resonance imaging (MRI) in conjunction with synchronized spirometry we analyzed and compared diaphragm movement during tidal breathing and voluntary movement of the diaphragm while breath holding. Breathing cycles of 16 healthy subjects were examined using a dynamic sequence (77 slices in sagittal plane during 20 s, 1NSA, 240x256, TR4.48, TE2.24, FA90, TSE1, FOV 328). The amplitude of movement of the apex and dorsal costophrenic angle of the diaphragm were measured for two test conditions: tidal breathing and voluntary breath holding. The maximal inferior and superior positions of the diaphragm were subtracted from the corresponding positions during voluntary movements while breath holding. The average amplitude of inferio-superior movement of the diaphragm apex during tidal breathing was 27.3+/-10.2 mm (mean +/- SD), and during voluntary movement while breath holding was 32.5+/-16.2 mm. Movement of the costophrenic angle was 39+/-17.6 mm during tidal breathing and 45.5+/-21.2 mm during voluntary movement while breath holding. The inferior position of the diaphragm was lower in 11 of 16 subjects (68.75 %) and identical in 2 of 16 (12.5 %) subjects during voluntary movement compared to the breath holding. Pearson's correlation coefficient was used to demonstrate that movement of the costophrenic angle and apex of the diaphragm had a linear relationship in both examined situations (r=0.876). A correlation was found between the amplitude of diaphragm movement during tidal breathing and lung volume (r=0.876). The amplitude of movement of the diaphragm with or without breathing showed no correlation to each other (r=0.074). The movement during tidal breathing shows a correlation with the changes in lung volumes. Dynamic MRI demonstrated that individuals are capable of moving their diaphragm voluntarily, but the amplitude of movement differs from person to person. In this study, the movements of the diaphragm apex and the costophrenic angle were synchronous during voluntary movement of the diaphragm while breath holding. Although the sample is small, this study confirms that the function of the diaphragm is not only respiratory but also postural and can be voluntarily controlled.     

Decision Tree in Working Memory Task Effectively Characterizes EEG Signals in Healthy Aging Adults

BackgroundThe changes in electroencephalogram (EEG) signals that reflect the changes in physiological structure, cognitive functions, and activities have been observed in healthy aging adults. It is unknown that when the brain aging initiates and whether these age-related alterations can be associated with incipient neurodegenerative diseases in healthy elderly individuals.Materials and methodsWe employed feature extraction and classification methods to classify and compare the EEG signals of middle-aged and elderly age groups. This study included 20 healthy middle-aged and 20 healthy elderly subjects. The EEG signals were recorded during a resting state (eyes-open and eyes-closed) and during a working memory (WM) task using eight electrodes. The minimum redundancy maximum relevance technique was employed in the selection of the optimal feature. Four classification methods, including decision tree, support vector machine, Naïve Bayes, and K-nearest neighbor, were used to distinguish the elderly age group from the middle-aged group based on their EEG signals.ResultsIn the resting state, a good correlation was observed among absolute power delta and theta bands and aging, whereas between beta absolute power and aging, a WM task correlation was observed. The results also indicated that the mean frequency and absolute power might be useful for the prediction and classification of EEG signals in aging individuals. Furthermore, the use of the decision tree method in a WM task state distinguished the elderly group from the middle-aged group with an accuracy of 87.5%.ConclusionsWorking memory could play a vital role in the optimization of classification of EEG signals in aging and discrimination of age-related issues associated with neurodegeneration.     

Resolving the dynamics of EEG generators by multichannel recordings

The voltage recorded over the cortex (ECoG) or over the scalp (EEG) is generated by currents derived from many sources called “generators”. Different patterns and amplitudes are observed in aroused, sleepy, epileptic or other brain states. Differences in amplitude are generally attributed to differences in synchrony among generators. The degree of EEG synchrony is measured by the correlation between electrodes placed over different cortical regions. We present a new way to quantitatively assess the degree of synchronization of these generators via multichannel recordings. We illustrate how situations where there are several groups of generators with different inter-group and intra-group synchronies can be analyzed. Finally, we present a way to identify the organization of groups exhibiting topographic organization. Although the model presented here is highly simplified, several methods are based on averaging activity over increasingly larger areas. These types of measurements may be applied as well to EEG and ECoG recordings.     

The link between cardiac autonomic activity and sleep delta power is altered in men with sleep apnea-hypopnea syndrome

We hypothesize that sleep apnea-hypopnea alters interaction between cardiac vagal modulation and sleep delta EEG. Sleep apnea-hypopnea syndrome (SAHS) is related to cardiovascular complications in men. SAHS patients show higher sympathetic activity than normal subjects. In healthy men, non-rapid eye movement (NREM) sleep is associated with cardiac vagal influence, whereas rapid eye movement (REM) sleep is linked to cardiac sympathetic activity. Interaction between cardiac autonomic modulation and delta sleep EEG is not altered across a life span nor is the delay between appearances of modifications in both signals. Healthy controls, moderate SAHS, and severe SAHS patients were compared across the first three NREM-REM cycles. Spectral analysis was applied to ECG and EEG signals. High frequency (HF) and low frequency (LF) of heart rate variability (HRV), ratio of LF/HF, and normalized (nu) delta power were obtained. A coherency analysis between HF(nu) and delta was performed, as well as a correlation analysis between obstructive apnea index (AI) or hypopnea index (HI) and gain, coherence, or phase shift. HRV components were similar between groups. In each group, HF(nu) was larger during NREM, while LF(nu) predominated across REM and wake stages. Coherence and gain between HF(nu) and delta decreased from controls to severe SAHS patients. In SAHS patients, the delay between modifications in HF(nu) and delta did not differ from zero. AI and HI correlated negatively with coherence, while HI correlated negatively with gain only. Apneas-hypopneas affect the link between cardiac sympathetic and vagal modulation and delta EEG demonstrated by the loss of cardiac autonomic activity fluctuations across shifts in sleep stages. Obstructive apneas and hypopneas alter the interaction between both signals differently.     

Linear correlation between fractal dimension of EEG signal and handgrip force

Fractal dimension (FD) has been proved useful in quantifying the complexity of dynamical signals in biology and medicine. In this study, we measured FDs of human electroencephalographic (EEG) signals at different levels of handgrip forces. EEG signals were recorded from five major motor-related cortical areas in eight normal healthy subjects. FDs were calculated using three different methods. The three physiological periods of handgrip (command preparation, movement and holding periods) were analyzed and compared. The results showed that FDs of the EEG signals during the movement and holding periods increased linearly with handgrip force, whereas FD during the preparation period had no correlation with force. The results also demonstrated that one method (Katz’s) gave greater changes in FD, and thus, had more power in capturing the dynamic changes in the signal. The linear increase of FD, together with results from other EEG and neuroimaging studies, suggest that under normal conditions the brain recruits motor neurons at a linear progress when increasing the force.     

EEG of the interstimulus intervals during habituation of auditory evoked potentials in depressive moods

Averaging of EEG of interstimulus intervals in the process of study of habituation of auditory evoked potentials (EPs) in healthy subjects and patients with endogenous depression, revealed a rhythmic wave process (RWP) especially expressed in patients. RWP appeared and became stronger in successive averaging of 10 realizations completing each of four series of 30 clicks; often (especially in depressive patients) it was manifest in averaging of all 120 realizations with an amplitude comparable with that of main EPs components and even greater. A significant correlation was found of RWP parameters with characteristics of melancholic mood in both subgroups. It is suggested that RWP appears as a result of regular changes of EEG background during multiple stimuli repetition in connection with increased "slow" habituation and in a special manifestation of perceptive defence during depression including mechanisms of active isolation from external world.