Development of psychomotor tempó (tapping speed and stability) and EEG alpha frequency in 7 to 15-years-old children

The psychomotor tempo (tapping) and its relation to alpha frequency was investigated in 100 7- to 15-year-old children. The frequency of alpha rhythm increased in proportion to age, and the maximum and preferential tapping frequencies revealed an increasing tendency, too. Mainly the preferential tapping frequency correlated with the age-dependent increment of EEG alpha frequency. Simultaneously, the variability of the tapping frequency decreased. During a phase of relatively stable tapping performance regular fluctuations in the tapping frequency occurred with a period duration between 0.67 and 13.3 s. These oscillations of the motor activity developed during ontogenesis: The slow fluctuations were found in all groups, whereas those with shorter periods were best pronounced in the older children. The development of EEG and psychomotor indices are assumed to be based on the morphological and functional maturation of the developing brain. Therefore, they may be used as a tool to assess the normal and disturbed brain development.     

Are acute changes after status epilepticus in immature rats persistent?

Early consequences of lithium-pilocarpine convulsive status epilepticus (SE) were studied six days after this status had been induced in rat pups at the age of either 12 or 25 days. Studies of spontaneous EEG activity demonstrated the presence of epileptic phenomena (isolated spikes) in both hippocampus and cortex (cortical spikes were more expressed in the older group). There were no marked behavioral correlates of spikes and transition into the ictal phase was exceptional. The motor performance on a rotorod and a horizontal bar was the same in experimental and control rats of both ages. Behavior in the open field was changed in a reverse manner in the two age groups: the locomotor activity of rats with induced seizures at the age of 12 days was significantly lower than that of their control siblings, whereas animals undergoing status at the age of 25 days were hyperactive. In addition, they also exhibited increased exploratory activity (rearing) and their habituation to the open field was deranged. Nissl-stained brain sections demonstrated extensive brain damage in the older group in contrast to the negative findings in younger animals. EEG, behavioral and morphological changes induced by status epilepticus in developing rats persisted for 6 days after the status. They markedly differed according to the age of animals.     

Timing of Intervention Affects Brain Electrical Activity in Children Exposed to Severe Psychosocial Neglect

Background

Early psychosocial deprivation has profound effects on brain activity in the young child. Previous reports have shown increased power in slow frequencies of the electroencephalogram (EEG), primarily in the theta band, and decreased power in higher alpha and beta band frequencies in infants and children who have experienced institutional care.

Methodology/Principal Findings

We assessed the consequences of removing infants from institutions and placing them into a foster care intervention on brain electrical activity when children were 8 years of age. We found the intervention was successful for increasing high frequency EEG alpha power, with effects being most pronounced for children placed into foster care before 24 months of age.

Conclusions/Significance

The dependence on age of placement for the effects observed on high frequency EEG alpha power suggests a sensitive period after which brain activity in the face of severe psychosocial deprivation is less amenable to recovery.     

High Resolution Topography of Age-Related Changes in Non-Rapid Eye Movement Sleep Electroencephalography

Sleeping brain activity reflects brain anatomy and physiology. The aim of this study was to use high density (256 channel) electroencephalography (EEG) during sleep to characterize topographic changes in sleep EEG power across normal aging, with high spatial resolution. Sleep was evaluated in 92 healthy adults aged 18–65 years old using full polysomnography and high density EEG. After artifact removal, spectral power density was calculated for standard frequency bands for all channels, averaged across the NREM periods of the first 3 sleep cycles. To quantify topographic changes with age, maps were generated of the Pearson’s coefficient of the correlation between power and age at each electrode. Significant correlations were determined by statistical non-parametric mapping. Absolute slow wave power declined significantly with increasing age across the entire scalp, whereas declines in theta and sigma power were significant only in frontal regions. Power in fast spindle frequencies declined significantly with increasing age frontally, whereas absolute power of slow spindle frequencies showed no significant change with age. When EEG power was normalized across the scalp, a left centro-parietal region showed significantly less age-related decline in power than the rest of the scalp. This partial preservation was particularly significant in the slow wave and sigma bands. The effect of age on sleep EEG varies substantially by region and frequency band. This non-uniformity should inform the design of future investigations of aging and sleep. This study provides normative data on the effect of age on sleep EEG topography, and provides a basis from which to explore the mechanisms of normal aging as well as neurodegenerative disorders for which age is a risk factor.     

Application of brain electric activity mapping for analysis of discharge propagation in epileptic patients

The brain electric activity mapping (BEAM) method was used for diagnostic purposes in patients who revealed the episodic paroxysmal activity in electroencephalographic records. The spectral features of brain spontaneous activity in the absence of the seizures demonstrated the topography similar to the seizure wave front propagation pathways observed in dynamic potential mapping. The cortical areas characterized by the increased ability to generate slow waves at certain frequencies revealed at the same time tendency for epileptic activity generation. The neuronal mechanism involved seems to be of resonance character as this correspondence is not observed when the power density distribution averaged in classical EEG frequency bands is analysed.     

Is the alpha rhythm a control parameter for brain responses?

 The main goal of the present study is to develop a conceptual analysis of alpha response in the brain based on single sweep evaluation. A new method was employed to estimate a set of single-sweep parameters and quantify the oscillatory behaviour of single, electroencephalograph (EEG) sweeps. It was aimed to demonstrate that brain alpha responses are governed by spontaneous alpha activity and to validate the principle of brain response excitability. Because the spontaneous alpha activity depends on both the topology of recording and the subject’s age, topology and age models were used. Spontaneous and evoked alpha activity were recorded at frontal and occipital sites in three groups of subjects: 3-year-old children, young adults and middle-aged subjects. Amplitude, enhancement and phase-locking of single alpha responses to visual stimuli were analysed. Major results showed that: (1) visual alpha responses could be recorded only if the alpha rhythm was developed in the spontaneous EEG independent of electrode location; (2) middle-aged adults showed more expressed frontal spontaneous alpha activity in comparison with young adults; (3) accordingly, alpha responses with higher amplitude and stronger phase-locking were produced over the frontal brain area in middleaged than young adults. These results validate the principle of brain response excitability and demonstrate that a shift towards frontal brain areas for both the spontaneous and evoked alpha activity occurs with increasing age in adults. The results are discussed in the context of the diffuse and distributed alpha system of the brain. Age-dependent changes in frontal alpha activity are suggested to be related to frontal brain functioning during aging. Received: 6 November 1995 / Accepted in revised form: 13 March 1997     

Electroencephalographic markers of the spontaneous recovery of the vertical posture in patients with consequences of traumatic brain injury

Nine patients (mean age, 23.6 ± 3.15 years) with a severe traumatic brain injury (TBI) associated with a loss of the ability to maintain vertical posture were enrolled in a comprehensive clinical and electroencephalographic study during the spontaneous recovery of vertical posture (VP). The patients were divided into three groups according to their functional deficit assessed on the international MPAI, FIM, and MMSE scales, which was determined by the severity of the TBI. The EEG data were compared to those of ten healthy subjects (mean age, 22.8 ± 0.67 years). In patients with a moderate impairment of the brain and a rapid recovery of VP (over two weeks), a change in the sitting position revealed EEG signs similar to reactive EEG restructurings of healthy individuals during the maintenance of VP in the form of a predominant EEG coherence increase in the right hemisphere for most of the rhythm bands; however, at this stage of VP recovery, the EEG restructurings retained pathological signs. In patients with a more severe functional deficit, spontaneous recovery of VP was accompanied by hyperreactive EEG restructurings for all rhythm bands without regional specificity. This finding showed up irrespective of the lateralization of the brain injury, which could be considered as a marker of positive dynamics of VP recovery. In patients with the most severe impairment and functional deficit and long-term (more than three months) absence of spontaneous VP recovery, the absence of reactive EEG restructurings was revealed in their passive verticalization, which could be used as a marker of negative prognosis.     

Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media

The resistive or non-resistive nature of the extracellular space in the brain is still debated, and is an important issue for correctly modeling extracellular potentials. Here, we first show theoretically that if the medium is resistive, the frequency scaling should be the same for electroencephalogram (EEG) and magnetoencephalogram (MEG) signals at low frequencies (<10 Hz). To test this prediction, we analyzed the spectrum of simultaneous EEG and MEG measurements in four human subjects. The frequency scaling of EEG displays coherent variations across the brain, in general between 1/f and 1/f ², and tends to be smaller in parietal/temporal regions. In a given region, although the variability of the frequency scaling exponent was higher for MEG compared to EEG, both signals consistently scale with a different exponent. In some cases, the scaling was similar, but only when the signal-to-noise ratio of the MEG was low. Several methods of noise correction for environmental and instrumental noise were tested, and they all increased the difference between EEG and MEG scaling. In conclusion, there is a significant difference in frequency scaling between EEG and MEG, which can be explained if the extracellular medium (including other layers such as dura matter and skull) is globally non-resistive.     

Study of the frequency parameters of EEG influenced by zone-dependent local ELF-MF exposure on the human head

It has been reported that human subjects exposed to electromagnetic fields exhibit changes in human EEG signals at the frequency of stimulation. The aim of the present study was to expose different parts of the brain to extremely low-frequency magnetic fields locally and investigate EEG power spectrum alters at the frequency of stimulation. EEG relative power spectrum were evaluated at 3, 5, 10, 17, and 45 Hz frequencies at T4, T3, F3, Cz, and F4 points, respectively, when these points were exposed to magnetic fields with similar frequencies and 100 μT intensity. The paired t-test results showed that power value of EEG did not alter significantly at the frequency of stimulation (P<0.05). Further, significant changes in different EEG bands caused by locally exposing to ELF-MF in different points of brain were observed. The changes in the EEG bands were not limited necessarily to the exposure point.     

Study of the frequency parameters of EEG influenced by zone-dependent local ELF-MF exposure on the human head

It has been reported that human subjects exposed to electromagnetic fields exhibit changes in human EEG signals at the frequency of stimulation. The aim of the present study was to expose different parts of the brain to extremely low-frequency magnetic fields locally and investigate EEG power spectrum alters at the frequency of stimulation. EEG relative power spectrum were evaluated at 3, 5, 10, 17, and 45 Hz frequencies at T4, T3, F3, Cz, and F4 points, respectively, when these points were exposed to magnetic fields with similar frequencies and 100 μT intensity. The paired t-test results showed that power value of EEG did not alter significantly at the frequency of stimulation (P < 0.05). Further, significant changes in different EEG bands caused by locally exposing to ELF-MF in different points of brain were observed. The changes in the EEG bands were not limited necessarily to the exposure point.     

Fractal dimension of electroencephalographic time series and underlying brain processes

 Fractal dimension has been proposed as a useful measure for the characterization of electrophysiological time series. This paper investigates what the pointwise dimension of electroencephalographic (EEG) time series can reveal about underlying neuronal generators. The following theoretical assumptions concerning brain function were made (i) within the cortex, strongly coupled neural assemblies exist which oscillate at certain frequencies when they are active, (ii) several such assemblies can oscillate at a time, and (iii) activity flow between assemblies is minimal. If these assumptions are made, cortical activity can be considered as the weighted sum of a finite number of oscillations (plus noise). It is shown that the correlation dimension of finite time series generated by multiple oscillators increases monotonically with the number of oscillators. Furthermore, it is shown that a reliable estimate of the pointwise dimension of the raw EEG signal can be calculated from a time series as short as a few seconds. These results indicate that (i) The pointwise dimension of the EEG allows conclusions regarding the number of independently oscillating networks in the cortex, and (ii) a reliable estimate of the pointwise dimension of the EEG is possible on the basis of short raw signals. Received: 1 September 1994/Accepted in revised form: 16 May 1995     

Heritability of human brain functioning as assessed by electroencephalography.

To study the genetic and environmental contributions to individual differences in CNS functioning, the electroencephalogram (EEG) was measured in 213 twin pairs age 16 years. EEG was measured in 91 MZ and 122 DZ twins. To quantify sex differences in the genetic architecture, EEG was measured in female and male same-sex twins and in opposite-sex twins. EEG was recorded on 14 scalp positions during quiet resting with eyes closed. Spectral powers were calculated for four frequency bands: delta, theta, alpha, and beta. Twin correlations pointed toward high genetic influences for all these powers and scalp locations. Model fitting confirmed these findings; the largest part of the variance of the EEG is explained by additive genetic factors. The averaged heritabilites for the delta, theta, alpha and beta frequencies was 76%, 89%, 89%, and 86%, respectively. Multivariate analyses suggested that the same genes for EEG alpha rhythm were expressed in different brain areas in the left and right hemisphere. This study shows that brain functioning, as indexed by rhythmic brain-electrical activity, is one of the most heritable characteristics in humans.     

EEG Spectral Characteristics in Junior Schoolchildren with Learning Problems

EEG spectral characteristics were studied in two age groups (7–8.5 and 8.5–10 years) of mentally healthy children and children with learning problems at rest and during performance of a Raven test. It was shown that slow frequencies are more pronounced in the EEG of 7- to 8.5-year-old children with learning problems than in EEG of healthy children of the same age group. An immature form of EEG activation, i.e., an increase not only in the but also in the frequencies during activity, was characteristic of these children. The reaction of the activation of the definitive type develops between the 8.5–10 years of age. This reaction is correlated with an increase in the efficiency of the sensory perceptive and sensorimotor activity. The distinctive feature of children with learning problems between 8.5–10 years of age is a greater expression of slow frequencies in the baseline EEG of the frontal (in particular, left frontal) areas of the cortex. The obtained results are considered as a reflection of a retardation of the functional maturation of the brain structures responsible for the deficit of involuntary and voluntary attention and the disorder of a systemic organization of perception and analytical–synthetic brain activity as compared to the normal age characteristics. Possible neurophysiological mechanisms responsible for learning problems in junior schoolchildren are discussed on the basis of the obtained results and evidence from the literature.     

Alpha-bursts and K-complex: phasic activation pattern during spontaneous recovery of correct psychomotor performance at difference stages of drowsiness

It is known that phasic activation processes reveal themselves by different electrophysiological patterns depending on the sleep depth. Alpha bursts are an electrophysiological manifestation of arousal at the initial stage of sleep, whereas at the II stage K-complex becomes the main arousal pattern. We have shown earlier that during light drowsiness spontaneous recovery of correct psychomotor test performance (after an error) by a sitting subject is accompanied by EEG alpha bursts. The aim of this work was to study the EEG phasic activation pattern at deeper drowsiness during test performance by a subject in a lying position. Subjects had to press sensitive button in a lying position with closed eyes with self-paced oral counting of pressings. The experiment lasted for 40 min; EEG, EOG, and button pressing were recorded. It was shown that recovery of correct performance after errors at deeper drowsiness was accompanied by two types of EEG phasic activation patterns (PAP-1 and PAP-2). The alpha frequency component was always present in both PAP-1 and PAP-2. PAP-1 were observed at early stages of drowsiness and consisted of high-amplitude alpha bursts and EEG activity of higher frequency. PAP-2 were recorded at deeper stages and consisted of K-complexes with superposition of PAP-1. At first (medium level of drowsiness) the alpha bursts were superposed on the late slow K-complex components. With further deepening of drowsiness the early fast components of K-complex were also observed. The early appearance of K-complex during test performance at drowsiness seems to be associated with the urgent run of brain arousal systems, which at spontaneous falling asleep are in operation at the II sleep stage.     

Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise

The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians'' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians'' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies.     

Mechanical properties of the dorsal fin muscle of seahorse (Hippocampus) and pipefish (Syngnathus)

The dorsal and pectoral fins are the primary locomotor organs in seahorses (Hippocampus) and pipefish (Syngnathus). The small dorsal fins beat at high oscillatory frequencies against the viscous medium of water. Both species are able to oscillate their fins at frequencies likely exceeding the point of flicker fusion for their predators, thus enhancing their ability to remain cryptic. High-speed video demonstrated that seahorse dorsal fins beat at 30-42 Hz, while pipefish dorsal fins oscillate at 13-26 Hz. In both species, the movement of the fin is a sinusoidal wave that travels down the fin from anterior to posterior. Mechanical properties of seahorse and pipefish dorsal fin muscles were tested in vitro by the work loop method. Maximum isometric stress was 176.1 kN/m(2) in seahorse and 111.5 kN/m(2) in pipefish. Work and power output were examined at a series of frequencies encompassing the range observed in vivo, and at a number of strains (percent length change during a contractile cycle) within each frequency. At a given strain, work per cycle declined with increasing frequency, while power output rose to a maximum at an intermediate frequency and then declined. Frequency and strain interacted in a complex fashion; optimal strain was inversely related to cycle frequency over most of the frequency range tested. Seahorse dorsal fin muscle was able to generate positive work at higher cycling frequencies than pipefish. Both species produced positive work at higher frequencies than have been reported for axial and fin muscles from other fish.     

Mutagenesis of a single AT basepair in mice transgenic for PhiX174 am3, cs70. II. Brain.

Most cell divisions in the mouse brain have ceased by 14 days after birth. Therefore, spontaneous mutations that occur in brain cells can be assumed to be fixed by replication during brain development. Spontaneous and ethylnitrosourea (ENU)-induced reverse mutations at a single AT base pair were measured in brain tissue by using mice transgenic for PhiX174 am3, cs70. The line (am54) has 50 PhiX genomes per haploid genome integrated in a tandem array and is maintained by random breeding on a C57BL/6 background. For mutagenesis studies, homozygous am54 males were mated to non-transgenic C57BL6/J females. Four-day old offspring from this cross were treated with 50 mg/kg ENU and were euthanized at 68-80 days of age. The ENU-treated animals had a significantly higher frequency of am3 revertants in brain than did concurrent controls. In a second experiment, hemizygous male offspring (85 to 94 days old) were treated with 150 mg/kg ENU and euthanized at various post-injection intervals (3, 10 and 110 days). The revertant frequencies 3 and 10 days after treatment were not significantly different from control values. At the 110 days post-injection interval, however, the average revertant frequency in the treated group was significantly lower than controls. In a second study animals were euthanized 3, 10 and 74 days after treatment. Two groups (3 and 74 days post-injection) also showed a significant decrease in the revertant frequency as compared to controls. Additional sets of adult animals were treated with 50 and 150 mg/kg ENU and were euthanized 195 to 201 days after treatment. The average revertant frequency of the animals that were treated with 50 or 150 mg/kg ENU was not significantly different from the control value. Thus, although an increase in mutant frequency is detected in the PhiX174 system when neonatal mice are treated with ENU, treatment of mature mice with ENU did not result in an increase in the mutant frequency. Moreover, under certain conditions, ENU-produced a significantly lower mutant frequency than was observed in the control animals. This decrease in the revertant frequency among the treated animals was likely due to selective killing of cells with a higher spontaneous revertant frequency than cells with lower frequency.     

Adaptive Filtering Methods for Identifying Cross-Frequency Couplings in Human EEG

Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.     

Brain connectivity at different time-scales measured with EEG

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.     

EEG in Children: Periodometric Analysis,Typology, and Age Peculiarities

We carried out a computer analysis of the EEG of 169 healthy schoolchildren (6 to 17 years old) with the use of a periodometric approach allowing us to obtain a number of quantitative indices that characterize the temporal structure of the analyzed EEG segment (histogram of distribution of the frequencies of EEG oscillations within the analyzed time period, indices of the different rhythms, and matrix of the probabilities of conversion from waves of one frequency range to waves of other ranges). We demonstrated that data of the periodometric analysis can be used for objective classification of EEG patterns. In children of different age groups, five types of background EEG activity were classified and described; we also demonstrated that the intragroup frequencies of these EEG types vary in healthy children with age. We discuss the advantages and disadvantages of the periodometric analysis of EEG, as well as the prospects and expediency of use of this analysis in physiological studies and in clinics.