Effect of caffeine and phenazepam on the quantitative parameters of the EEG and ultraslow electrical processes in the brain

A comparative study of the power and coherence of the ultraslow phasic processes (USPPs) of the brain in the frequency range 0.05–0.5 Hz and the EEG (1.5–50 Hz) at rest with the eyes opened or closed before and after the administration of caffeine and phenazepam, a benzodiazepine tranquilizer, was performed. Caffeine and phenazepam caused similarly directed changes in the EEG pattern. The differences between the effects of these drugs were expressed in a different topography of changes in the EEG pattern. Different locations of such changes are supposed to reflect differences in the behavioral effects of drugs (stimulating or sedative). According to the USPP data, the differences in the drug effects are accompanied not only by a different topography of changes in the USPP pattern, but also by an opposite direction of these changes. This fact makes it possible to suppose that, during pharmacological tests, the differential sensitivity of USPPs as an indicator of CNS sensitivity may be higher than that of the EEG, in view of the closer relationship between the behavioral and electrographic changes.     

Frequency-Dependent Modulation of Regional Synchrony in the Human Brain by Eyes Open and Eyes Closed Resting-States

The eyes-open (EO) and eyes-closed (EC) states have differential effects on BOLD-fMRI signal dynamics, affecting both the BOLD oscillation frequency of a single voxel and the regional homogeneity (ReHo) of several neighboring voxels. To explore how the two resting-states modulate the local synchrony through different frequency bands, we decomposed the time series of each voxel into several components that fell into distinct frequency bands. The ReHo in each of the bands was calculated and compared between the EO and EC conditions. The cross-voxel correlations between the mean frequency and the overall ReHo of each voxel’s original BOLD series in different brain areas were also calculated and compared between the two states. Compared with the EC state, ReHo decreased with EO in a wide frequency band of 0.01–0.25 Hz in the bilateral thalamus, sensorimotor network, and superior temporal gyrus, while ReHo increased significantly in the band of 0–0.01 Hz in the primary visual cortex, and in a higher frequency band of 0.02–0.1 Hz in the higher order visual areas. The cross-voxel correlations between the frequency and overall ReHo were negative in all the brain areas but varied from region to region. These correlations were stronger with EO in the visual network and the default mode network. Our results suggested that different frequency bands of ReHo showed different sensitivity to the modulation of EO-EC states. The better spatial consistency between the frequency and overall ReHo maps indicated that the brain might adopt a stricter frequency-dependent configuration with EO than with EC.     

Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchronization

The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome.     

Detecting Static and Dynamic Differences between Eyes-Closed and Eyes-Open Resting States Using ASL and BOLD fMRI

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain.     

Coupling between Intrinsic Prefrontal HbO2 and Central EEG Beta Power Oscillations in the Resting Brain

There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration [Formula: see text] s) between prefrontal oxyhemoglobin (HbO2) in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence [Formula: see text]) between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (de)oxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains' motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007).     

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful.     

Alpha blocking and 1/fβ spectral scaling in resting EEG can be accounted for by a sum of damped alpha band oscillatory processes

The dynamical and physiological basis of alpha band activity and 1/f^β noise in the EEG are the subject of continued speculation. Here we conjecture, on the basis of empirical data analysis, that both of these features may be economically accounted for through a single process if the resting EEG is conceived of being the sum of multiple stochastically perturbed alpha band damped linear oscillators with a distribution of dampings (relaxation rates). The modulation of alpha-band and 1/f^β noise activity by changes in damping is explored in eyes closed (EC) and eyes open (EO) resting state EEG. We aim to estimate the distribution of dampings by solving an inverse problem applied to EEG power spectra. The characteristics of the damping distribution are examined across subjects, sensors and recording condition (EC/EO). We find that there are robust changes in the damping distribution between EC and EO recording conditions across participants. The estimated damping distributions are found to be predominantly bimodal, with the number and position of the modes related to the sharpness of the alpha resonance and the scaling (β) of the power spectrum (1/f^β). The results suggest that there exists an intimate relationship between resting state alpha activity and 1/f^β noise with changes in both governed by changes to the damping of the underlying alpha oscillatory processes. In particular, alpha-blocking is observed to be the result of the most weakly damped distribution mode becoming more heavily damped. The results suggest a novel way of characterizing resting EEG power spectra and provides new insight into the central role that damped alpha-band activity may play in characterising the spatio-temporal features of resting state EEG.     

Directional Connectivity between Frontal and Posterior Brain Regions Is Altered with Increasing Concentrations of Propofol

Recent studies using electroencephalography (EEG) suggest that alteration of coherent activity between the anterior and posterior brain regions might be used as a neurophysiologic correlate of anesthetic-induced unconsciousness. One way to assess causal relationships between brain regions is given by renormalized partial directed coherence (rPDC). Importantly, directional connectivity is evaluated in the frequency domain by taking into account the whole multichannel EEG, as opposed to time domain or two channel approaches. rPDC was applied here in order to investigate propofol induced changes in causal connectivity between four states of consciousness: awake (AWA), deep sedation (SED), loss (LOC) and return of consciousness (ROC) by gathering full 10/20 system human EEG data in ten healthy male subjects. The target-controlled drug infusion was started at low rate with subsequent gradual stepwise increases at 10 min intervals in order to carefully approach LOC (defined as loss of motor responsiveness to a verbal stimulus). The direction of the causal EEG-network connections clearly changed from AWA to SED and LOC. Propofol induced a decrease (p = 0.002–0.004) in occipital-to-frontal rPDC of 8-16 Hz EEG activity and an increase (p = 0.001–0.040) in frontal-to-occipital rPDC of 10–20 Hz activity on both sides of the brain during SED and LOC. In addition, frontal-to-parietal rPDC within 1–12 Hz increased in the left hemisphere at LOC compared to AWA (p = 0.003). However, no significant changes were detected between the SED and the LOC states. The observed decrease in back-to-front EEG connectivity appears compatible with impaired information flow from the posterior sensory and association cortices to the executive prefrontal areas, possibly related to decreased ability to perceive the surrounding world during sedation. The observed increase in the opposite (front-to-back) connectivity suggests a propofol concentration dependent association and is not directly related to the level of consciousness per se.     

EEG differences between resting states with eyes open and closed in darkness

Transition from a resting state with eyes closed (REC) to a resting state with eyes open (REO) is associated with visible changes in EEG, which are traditionally considered to be a sign of reorganization of the brain’s activity in response to visual stimuli. The EEGs recorded in the REC and REO states in complete darkness, when the stimulatory effect of light to the eye’s retina was absent, were compared. Thirty healthy subjects participated in the study. EEG in the range of 1.5–50 Hz was recorded from nineteen zones of the head monopolarly. It was found that, under conditions of complete darkness, the REC and REO states significantly differed in their EEG spectral power and coherence in the Δ, θ, α₁, α₂, β₁, β₂ and γ frequency bands. Under experimental conditions, these changes in the EEG could not be induced by external influence to the visual system. Therefore, we suppose that they are correlates of the switching of involuntary preliminary attention from internally directed attention specific for the REC state to externally directed attention specific for the REO state.     

The age-related characteristics of the organization of brain electrical activity in 7- to 14-year-old schoolchildren with neuroses in different functional states

By the method of factor analysis characteristics of functional brain states in children and juveniles of different age with neuroses were studied by EEG data. Similarity was established of the patients EEG structure at strained and emotional states. In the studied period of individual development (7-14 years) the most expressed changes of background EEG were observed at the age og 9-12 years. At functional loads, beginning from the age of 9-10, insufficient activity of the frontal region of the left hemisphere was found. The greatest changes of the EEG integral characteristics were observed in patients with vegetative-emotional disturbances and the smallest-at verbal-motor ones.     

Electrophysiological correlates of rest and activity in Drosophila melanogaster

Extended periods of rest in Drosophila melanogaster resemble mammalian sleep states in that they are characterized by heightened arousal thresholds and specific alterations in gene expression. Defined as inactivity periods spanning 5 or more min, amounts of this sleep-like state are, as in mammals, sensitive to prior amounts of waking activity, time of day, and pharmacological intervention. Clearly recognizable changes in the pattern and amount of brain electrical activity accompany changes in motor activity and arousal thresholds originally used to identify mammalian sleeping behavior. Electroencephalograms (EEGs) and/or local field potentials (LFPs) are now widely used to quantify sleep state amounts and define types of sleep. Thus, slow-wave sleep (SWS) is characterized by EEG spindles and large-amplitude delta-frequency (0-3.5 Hz) waves. Rapid-eye movement (REM) sleep is characterized by irregular gamma-frequency cortical EEG patterns and rhythmic theta-frequency (5-9 Hz) hippocampal EEG activity. It is unknown whether rest and activity in Drosophila are associated with distinct electrophysiological correlates. To address this issue, we monitored motor activity levels and recorded LFPs in the medial brain between the mushroom bodies, structures implicated in the modulation of locomotor activity, of Drosophila. The results indicate that LFPs can be reliably recorded from the brains of awake, moving fruit flies, that targeted genetic manipulations can be used to localize sources of LFP activity, and that brain electrical activity of Drosophila is reliably correlated with activity state.     

Spatial organization of EEG activity during active hyperventilation (cyclic breath) I. general patterns of changes in brain functional state and the effect of paroxysmal activity

Changes in spatial organization of EEG activity were analyzed in 44 humans during active 1-h hyperventilation using cyclic or circular breath (CB) technique similar to rebirthing breath technique. The dynamics of different indices was recorded each 5 min (using 12 time slots). A double-humped pattern of changes in spatial organization indices (linear processes) and spatial disorder (nonlinear processes) of biopotentials: an initial decrease within 1 to 20–30 min and a second one from 35–40 min to the end of session. A complex dynamics of spatial frequency processes (coherence and spectral power of biopotentials) with different pattern of changes within narrow frequency EEG bands. The dynamics of the spatial organization of EEG indices proved to depend on the intensity of hyperventilation-induced paroxysmal activity. The indices of spatial synchronization and disorder of biopotentials as well as low frequency β-activity (16.00–22.50 Hz) decreased more at the background of high rather than low paroxysmal activity, while the low frequency components (Δ and Θ) and high frequency α-activity (11.25–12.50 Hz) increased more. The obtained data are considered in terms of specific consciousness state induced by CB.     

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 characteristics of cognitive-specific alerting attention in verbal learning: I. Characteristics of EEG local synchronization

The EEG was recorded in 19 standard derivations in 88 students in the following states: rest with the eyes open, memorization (learning) of bilingual verbal semantic pairs (Latin and Russian), and retrieval (check) of the learned information. In order to calculate the mean heart rate (HR) in each state, the electrocardiogram was recorded. The subjective difficulty of task performance was assessed. Statistical comparison of the spectral power estimates in these states for frequency bands θ (4–7 Hz), α₁ (7–10 Hz), α₂ (10–13 Hz), β₁ (13–18 Hz), β₂ (18–30 Hz), and γ (30–40 Hz) demonstrated a number of significant differences in the EEG absolute power (local synchronization) between the states reproducible in subgroups. Comparison of the states of memorization and retrieval showed that, in the state of memorization, the EEG power in the γ, β₂, and θ bands was significantly lower throughout the cortical surface. Comparison of the active states with the reference state of rest showed that, in both active states, changes in the EEG power were of the same direction in the majority of the frequency bands (an increase in the θ, β₂, and γ bands and a decrease in the α₂ band) except α₁, in which memorization was predominantly accompanied by a decrease in the power, whereas retrieval was associated with an increase. No significant differences were found between the states of memorization and retrieval in the HR or the subjective estimate of task difficulty. The results can be interpreted as a reflection of cognitive-specific forms of general preparatory attention.     

Effects of 45-Hz magnetic fields on the functional state of the human brain

The influence of sinusoidal 45-Hz magnetic fields on the brain functions of 20 volunteers was investigated in a double-blind study using spectral analysis of EEG and measurements of Omega potentials and reaction time (RT). The field strength was 1,000 A/m (1.26 mT) and the duration of exposure was 1 h. Ten volunteers were exposed to a continuous field and ten received an intermittent exposure (1 s on/1 s off). Each person received one real and one sham exposure. One half of the volunteers got the real exposure first and the sham treatment after at least 24 h. For the rest, the sequence was inverse. The measurements of EEG, omega potentials and RT were performed before and after each exposure. Several statistically significant changes were observed, most of them after intermittent exposure. In the EEG, an increase of alpha (7.6–13.9 Hz) activity and a decrease of delta (1.5–3.9 Hz) activity were observed. β waves (14.2–20 Hz) increased in the frontal derivations as did the total power in occipital derivations. The mean and peak frequencies of EEG increased mainly in the frontal derivations. No direct effects on RT were seen. Learning to perform the RT test (decrease of RT in repeated trials), however, seemed to be affected by the exposure. The persons who received real exposure first learned more slowly than those who got sham exposure first. Further experiments are necessary to confirm the findings and for understanding the mechanisms of the effects. © 1993 Wiley-Liss. Inc.     

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.     

Dynamics of the gamma-responses in an 8-second interval between facial and trigger stimuli as dependent the success of task performance

A cognitive set to facial expression was used as a model with the loading on working memory being increased by increasing the interval between the facial and triggering stimuli to 8 seconds. The aim was to determine whether the intensity of brain potentials evoked in a range of 41–60 Hz (the range 15–60 Hz was used) by facial stimuli is associated with the “success” of task performance (mistake rate). An index of average amplitudes of EEG oscillations was used to measure the response to facial stimuli, and γ responses proved to be associated with the number of mistakes in performing the task. The results make it possible to consider the γ responses to facial stimuli as an EEG correlate of the internal states that correspond to adequate actions of the subject in the test with a 8-s interval between the facial and trigger stimuli.     

EEG beta and gamma powers when comparing certain psychophysiological states with normal and weakened electromyogram of facial muscles

With the advancement of contemporary techniques for studies of high-frequency electroencephalograms (EEGs), possible contamination of the EEG with the electromyogram (EMG) of pericranial muscles has raised more and more concern. The aim of the present study was to demonstrate if certain EEG correlates of mental activities can be revealed in a high-frequency scalp EEG in spite of EMG contamination. Nineteen healthy women who performed similar test tasks before and after cosmetic injections of Dysport in various facial regions for reduction of the activity of facial muscles took part in the study. Inductions of emotional states with different valences, memory storing, and extraction of verbal information were used in the test tasks. The default state of rest was examined as well. During performance of the tasks, parallel registrations of the EEG from the scalp surface (19 channels) and EMG from several facial muscles (6 channels) were carried out. Changes in the spectral power in β₂ and low γ frequency bands (18–40 Hz) in EEG- and EMG-derivations after Dysport injections were analyzed. Changes in the spectral power in the same bands in pairwise comparisons for the test tasks before and after Dysport injections were also analyzed separately. It was demonstrated that Dysport injections lead to reduction of the EMG power in areas of the injections and to reduction of EEG power in the frontal and temporal derivations. However, the EEG-correlates revealed when comparing different test tasks remained qualitatively invariable as for after and before Disport injections. These facts confirm that EMG makes a noticeable contribution to the electric activity registered from the scalp in the frequency ranges greater than 18 Hz. At the same time, one can see that at least in certain experimental situations the influence of EMG does not make impossible identification of EEG-correlates of mental activity with EEG registration from the head surface at least in the β₂ and low γ frequency bands (18–40 Hz).     

The effects of centrally acting drugs on the EEG correlates of meditation.

The present study investigated the effects of three centrally acting drugs on the significant increase in the intermediate alpha frequency of the electroencephalogram (EEG) that accompanied meditation in a male volunteer. When compared to the EEG recorded before each of the three drugs was administered, naloxone tended to enhance the increase in the power of the intermediate alpha EEG (9.4-10.4 Hz), while diazepam tended to spread the increase to the slow (7.4-9.4 Hz) alpha EEG, and flumazenil was without much effect on the overall EEG pattern. However, these EEG changes when compared to similar changes obtained with saline administration were not significantly different from the latter. Thus, it is unlikely that the EEG correlates of meditation are causally related to the rise or fall of endogenous opioid peptides or benzodiazepinelike substances in the brain.     

Exploring Age-Related Changes in Dynamical Non-Stationarity in Electroencephalographic Signals during Early Adolescence

Dynamics of brain signals such as electroencephalogram (EEG) can be characterized as a sequence of quasi-stable patterns. Such patterns in the brain signals can be associated with coordinated neural oscillations, which can be modeled by non-linear systems. Further, these patterns can be quantified through dynamical non-stationarity based on detection of qualitative changes in the state of the systems underlying the observed brain signals. This study explored age-related changes in dynamical non-stationarity of the brain signals recorded at rest, longitudinally with 128-channel EEG during early adolescence (10 to 13 years of age, 56 participants). Dynamical non-stationarity was analyzed based on segmentation of the time series with subsequent grouping of the segments into clusters with similar dynamics. Age-related changes in dynamical non-stationarity were described in terms of the number of stationary states and the duration of the stationary segments. We found that the EEG signal became more non-stationary with age. Specifically, the number of states increased whereas the mean duration of the stationary segment decreased with age. These two effects had global and parieto-occipital distribution, respectively, with the later effect being most dominant in the alpha (around 10 Hz) frequency band.