Differences in EEG alpha activity related to giftedness

In three experiments, differences in EEG alpha activity between gifted (mean IQ = 137) and average (mean IQ = 105) individuals were investigated. EEG activity was monitored over 16 scalp locations. A fast Fourier transform was performed on 15 artifact-free 2-second chunks of data to derive a spectral power average in the alpha band (7.5–13 Hz). In the first experiment, EEG of gifted and average individuals during two relaxation phases—eyes closed and eyes open—was recorded. Gifted individuals showed higher EEG alpha power only while resting with eyes open. In the second experiment, gifted and average individuals solved two problems that were divided into phases of problem solving and preparing for problem solving (reading, making a plan of how to solve the problem). Significant differences were obtained only for the problem-solving stages. Gifted individuals in comparison with average ones showed higher alpha power (less mental effort) while solving the two problems. The third experiment investigated whether the lower mental activity displayed by gifted individuals was related to their ability to form more abstract schemata. For that purpose EEG was recorded while gifted and average individuals memorized lists of words and pictures that either allowed, or did not allow, for classification into more abstract categories. For both types of lists, gifted individuals displayed higher alpha power than average ones. The results obtained confirm the hypothesis that the higher EEG alpha power during information processing displayed by gifted individuals may derive from the nonuse of many brain areas not required for the problem at hand.     

Slow alpha in the EEG power spectrum as an indicator for conceptual arousal]

Based on previous findings (B?sel et al., 1990) it was assumed that in concept learning tasks generating on hypotheses on a concept which has to be developed is accompanied by increases of the Alpha 1 power (7.5-10 Hz) in the spontaneous EEG activity. In this study 16 subjects performed five problem solving tasks with similar processing requirements. EEG data were analyzed by means of post hoc comparisons of subjects differing in performance quality. Additionally, four control tasks were employed in which, based on previous studies, variations in the Theta frequency range were expected. An effect in the Alpha 1 frequency band was observed in tasks requiring reconstructive recall or testing the usefulness of an mathematical algorithm. The creation of a rank order or mental map is accompanied by power increases in the lower portions of the Alpha 1 frequency band (7.5-8.5 Hz). Moreover a high amount of controlled variance (eta2 up to 34%) was obtained for this effect. Increases in EEG Theta power, which presumably indicate subjects' component analysis, were found before the subjects recognized parts of geometric figures or before relevant features in the "buddhist monk problem" were discriminated. The dynamics of EEG power over time is in examples of frequency/time plots in a figure, illustrated.     

Just a minute meditation: Rapid voluntary conscious state shifts in long term meditators

Meditation induces a modified state of consciousness that remains under voluntary control. Can meditators rapidly and reversibly bring about mental state changes on demand? To check, we carried out 128 channel EEG recordings on Brahma Kumaris Rajayoga meditators (36 long term: median 14240 h meditation; 25 short term: 1095 h) and controls (25) while they tried to switch every minute between rest and meditation states in different conditions (eyes open and closed; before and after an engaging task). Long term meditators robustly shifted states with enhanced theta power (4–8 Hz) during meditation. Short term meditators had limited ability to shift between states and showed increased lower alpha power (8–10 Hz) during eyes closed meditation only when pre and post task data were combined. Controls could not shift states. Thus trained beginners can reliably meditate but it takes long term practice to exercise more refined control over meditative states.     

Sensorimotor EEG operant conditioning: Experimental and clinical effects

Neurophysiological studies in cats have established a functional relationship between waking 12–15 Hz sensorimotor cortex rhythmic EEG activity (the sensorimotor rhythm or SMR) and a similar pattern during sleep, the sleep spindle. Both result from oscillatory thalamocortical discharge involving ventrobasal thalamus and sensorimotor cortex, and both are associated with a state of suppressed motor excitability. Enhancement of the SMR with operant conditioning methods in the cat clearly led to reduced seizure susceptibility. The experimental application of this approach to seizure control in epileptics has resulted in (A) evidence that EEG patterns can be manipulated significantly in man with operant conditioning, (B) suggestive observations concerning a potential component of pathology in epilepsy, and (C) strong preliminary evidence that SMR operant conditioning in epileptics is specifically therapeutic. Current research has focused upon the EEG during sleep in epileptics with primary motor symptomatology. This measure often reveals several hard signs of pathology. These include the presence of abnormal activity in the 4–7 Hz frequency band and the absence or disturbance of activity in the 11–15 Hz frequency band. Power spectral analysis is being utilized to quantify these sleep EEG components in five groups of epileptic patients, studied with different frequency patterns rewarded in an A-B-A design which provides for counterbalancing of order effects. Initial laboratory training is followed by 9–12 months of training at home with portable feedback equipment. Reward contingencies are reversed within each group at approximately three month intervals. Clinical EEG data, blood anticonvulsant measures and patient seizure logs supplement sleep EEG data obtained before training and after each phase of the design. Early results have again indicated specific therapeutic benefits following training of high frequency rhythmic central cortical activity.     

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect

fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ EEG. However, there has been no verification that these modalities provide converging information at the individual subject level. The present study examined simultaneous EEG and fMRI in healthy volunteers during six mental imagery tasks to determine whether one mental imagery task generates more robust activation across subjects; whether activation can be predicted from familiarity with the imagined activity; and whether EEG and fMRI converge upon the same conclusions about individual imagery performance. Mental arithmetic generated the most robust activation in the majority of subjects for both EEG and fMRI, and level of activation could not be predicted from familiarity, with either modality. We conclude that overall, EEG and fMRI agree regarding individual mental imagery performance.     

Hemispheric lateralization of the EEG during wakefulness and REM sleep in young healthy adults

EEG recordings confirm hemispheric lateralization of brain activity during cognitive tasks. The aim of the present study was to investigate spontaneous EEG lateralization under two conditions, waking and REM sleep. Bilateral monopolar EEG was recorded in eight participants using a 12-electrode montage, before the night (5 min eyes closed) and during REM sleep. Spectral analysis (0.75-19.75 Hz) revealed left prefrontal lateralization on total spectrum amplitude power and right occipital lateralization in Delta activity during waking. In contrast, during REM sleep, right frontal lateralization in Theta and Beta activities and right lateralization in occipital Delta activity was observed. These results suggest that spontaneous EEG activities generated during waking and REM sleep are supported in part by a common thalamo-cortical neural network (right occipital Delta dominance) while additional, possibly neuro-cognitive factors modulate waking left prefrontal dominance and REM sleep right frontal dominance.     

Interindividual differences in alpha and theta power reflect memory performance

Previous research from our laboratory has shown that phasic or event-related changes in alpha and theta band power are related to memory performance. In this study, we test the hypothesis, whether tonic or ‘baseline’ power too is related to memory performance. The ongoing EEG was analyzed for a sample of 60 subjects during five experimental conditions: eyes closed, eyes open, memorizing words and counting backward in steps of 3 and 7. The results show that subjects with good memory performance have significantly larger upper alpha, but less theta and lower alpha power. In contrast to memory, good calculation performers have more beta and theta power than bad performers. These findings were obtained during actual task performance, but in a similar way also during the resting conditions eyes closed and open.     

Changes in the EEG frequency spectrum in various phases of mental stress

To obtain evidence about the relationship between spontaneous EEG activity and mental activity, an experiment was designed and executed with EEG recordings during a concept-learning task. We varied task performance (self-paced vs. machine-paced) and distinguished different stages of information processing during task performance. Using factor analysis calculated on all spectral coefficients, we found two orthogonal variables in the clinical alpha band. Alpha 2 power (10.5-12 Hz) seems to reflect the overall processing demands imposed on the individuals. Furthermore, there are different EEG frequency patterns during perceptual-central- compared with response-related processing as well as during processing of positive vs. negative feedback. The results suggest using (1) conservative procedures in hypothesis testing and (2) procedures to reduce between subject variability (a posteriori defined frequency variables, relative power values, scaling of reaction values) in further studies relating EEG activity to mental activity during task performance.     

Evening and morning EEG differences between young men and women adults

Evening and morning waking EEG (eyes closed) was recorded in 16 women and 13 men aged 18-26 years old. Participants were fitted with a 13-electrode montage (Fp1, Fp2, FZ, F7, F8, C3, C4, T3, T4, P3, P4, O1, and O2) referred to linked ears. For each recording electrode, EEG total spectral amplitude power (microV/Hz, 0.75-19.75 Hz) was compared using 2 (Gender) x 2 (Moments) analyses of variance for repeated measures and LSD post-hoc tests. We found significant simple Gender effects, with women displaying higher EEG values for Central, Frontal, Parietal, and left Temporal leads. Simple Moment effects were also found, with lower morning values in Temporal and left Frontal recording sites. A Gender x Moment interaction was found at the right Frontal recording site. No significant effects were found for Prefrontal and Occipital recording sites, whatsoever. These results bring new understandings of gender and time of day effects in waking EEG and point to different sensitivity in different cortical areas. The present results could explain some of the observations related to gender differences in cognitive performance.     

Maturation of EEG power spectra in early adolescence: a longitudinal study

This study investigated the fine-grained development of the EEG power spectra in early adolescence, and the extent to which it is reflected in changes in peak frequency. It also sought to determine whether sex differences in the EEG power spectra reflect differential patterns of maturation. A group of 56 adolescents were tested at age 10 years and then at two further time-points approximately 18 months apart. The EEG was recorded during both eyes-closed and eyes-open conditions and Fourier transformed to provide estimates of absolute and relative spectral power at 0.5 Hz intervals from 0.5 to 40 Hz. The peak alpha frequency for each individual at each time-point was also determined for relative spectral power. Partial Least Squares (PLS) analysis was used to determine the combination of electrodes and frequencies that showed developmental change, or differed between the sexes. As a function of age, absolute delta and theta frequencies power decreased, and relative alpha2 and beta frequencies increased, replicating the standard findings of a decrease in lower, and increase in higher, frequencies with age. A small but significant increase in peak alpha frequency with age was detected. Moreover PLS analysis performed with individual alpha frequencies aligned to 10 Hz suggested that the age-related increase seen in alpha2 relative power was driven by changes in the peak frequency. Although males demonstrated higher alpha power than females, there were no sex differences in peak frequency, suggesting that there may be more to sex differences in EEG power than simply different rates of maturation between the two sexes.     

Idioventricular low frequency oscillation in QT interval responds univocally to RR confusing kinds of mental stress.

Seventeen male subjects, aged nineteen to twenty, went through a protocol including, while supine, relaxation at rest (10 min) and mental stress (MS) by a Kraepelin (arithmetic) test (5 min), as part of a larger study. With a polygraphic analog recording set-up we also collected a 1 ms - digital facsimile of a lead II-like thoracic ECG with maximum T-wave (Codas, Dataq Instr). Twenty-three stress responses were assigned to three classes according to known cardiotacho-, plethysmo-, and pneumo-graphic marks of "concentrated attention mainly," "emotion," or still "high emotion." During each setting the most stationary 3 min RR epoch in cardiotachogram was selected for joint RR & QT beat-by-beat variability study. RR and QT intervals were detected using a published algorithm. Conventional RR and QT Fourier autospectra were computed, while using RR*QT mean square coherence spectrum we detached the RR-independent, idioventricular (IV) fraction of QT low frequency (LF: 0.04-0.15 Hz) power of variability (IV QT-LF). IV QT-LF responded consistently to varieties of mental stress that confuse RR-LF or let QT-LF unchanged, best witnessing the cortically-issued ventricular adrenergic strain. Indeed, while emotion propels the same way all spectral variables above, concentrated attention increased (Wilcoxon) significantly IV QT-LF only (0.54-0.80 ms2) and decreased RR-LF (715-463 ms2). Findings hold promise of a non-invasive, high resolution Holter based monitoring of sympathetic status of myocardium, robust vis-à-vis of confusion caused by the autonomic interplay at sino-atrial node.     

Multivariate discriminant analysis of EEG power spectra in acute schizophrenic patients and healthy probands

The electroencephalogram (EEG) during information processing is influenced by specific changes in brain electrical activity. Based on the theory of a disturbed information processing in schizophrenics we analysed auditory stimulus induced EEG changes by Fast Fourier Transformation. The most important of the significant stimulation dependent EEG power changes were measured in the 0.5-3.5 Hz and 10-13.5 Hz frequency bands in the left parietal lead. In a multivariate analysis the separation of the subjects examined into acute schizophrenics and normals was incorrect in only 21% of the cases (resubstitution rate): using the pi-method an error of 31% was estimated.     

Correlation between evening and morning waking EEG and spatial orientation

The prefrontal, frontal, and parietal EEG of 16 healthy young adults (seven men, nine women; age=22.57+/-4.2) was recorded during the waking state (eyes closed) in the evening before and the morning following a second consecutive night spent in a sleep laboratory. Following the morning EEG recording session, participants were tested in a human-size maze upon five learning trials of a four-intersection route. Results on the fifth trial served as the learning index. We found a significant positive correlation between time taken to carry out the route and prefrontal, frontal EEG alpha-2 (10.0-12.75 Hz), and sigma (11.5-14.5 Hz) frequency bands. We also found that prefrontal and frontal theta activity correlated negatively with number of errors. No correlation was found between performance and neither alpha-1 (8.0-9.75 Hz) nor parietal EEG activity. These results confirm the involvement of the prefrontal and frontal cortices in the mechanisms responsible for modulating spatial orientation.     

The long‐term effects of institutional rearing,foster care intervention and disruptions in care on brain electrical activity in adolescence

Exposure to early psychosocial deprivation as a result of institutional care disrupts typical brain development. The Bucharest Early Intervention Project (BEIP) is the first longitudinal study to investigate the neurodevelopment of institutionalized infants randomized to a foster care (FCG) intervention versus care as usual (CAUG). Here, we present findings from a follow‐up assessment of brain electrical activity as indexed by resting EEG at age 16 years. In addition, we examined the effects of disruption of foster care placement (e.g. the number of moves among foster care placements) on brain electrical activity. Resting‐state EEG was collected from 48 CAUG, 46 FCG and 48 never institutionalized (NIG) control participants. Absolute (µV²) and relative (proportion) power were computed from eyes closed, resting EEG data for theta, alpha and beta frequency bands. The CAUG displayed higher relative theta and lower relative alpha power compared to the FCG at 16 years of age. The FCG showed brain activity comparable to the NIG. The results further showed that disruptions following the original foster care placement had an adverse effect on brain electrical activity. Within the foster care group, there were no effects of age of placement on EEG power. Placement of children who have experienced early institutional rearing into stable foster care settings ensure long‐term improvement in brain functioning.     

Interhemispheric EEG activity in normal and aphasic adults.

EEG recordings were obtained from 10 normal and 10 aphasic adults while they participated in behavioral tasks and a no performance condition. Interhemispheric asymmetry and average activity at 5 to 15 Hz in each hemisphere were compared between groups and among tasks. Asymmetry during behavioral tasks did not differ significantly between groups or among tasks, however, aphasic patients showed a significant decrease in average activity at 5 to 15 Hz on the behavioral tasks compared with the level for a non performance condition. Test-retest reliability was poor for asymmetry but acceptable for average activity at 5 to 15 Hz. Finally, asymmetry was significantly related with severity of aphasia.     

心算加工年老化及其机制研究

以172名20－79岁成人为被试对心算加工的年老化过程及其机制进行了研究。任务为连续减法心算,依难度分为5种：1000－1、1000－3、1000－7、1000－13及1000－17。结果表明,年龄与心算难度存在明显的交互作用,且随着年龄增加,不同难度心算效率均以幂函数形式降低。结构方程建模分析发现心算加工年老化过程存在两个中介作用因子,即速度因子和非速度因子,且速度因子对非速度因子存在明显的正效应。     

Evaluation of human consciousness level by means of “automated fluctuation analysis” of high frequency electroencephalogram fitted by double Lorentzians

Since Berger’s discovery of the electroencephalogram (EEG), its analysis has been generally restricted to the visual range (upmost 100Hz) and has ignored higher frequency components. One reason should be that there are no reliable methods to distinguish the brain potentials from muscle activity. We have introduced fluctuation analysis, which is popular method especially in the field of basic physiology to clinical electrophysiology. In our previous study, it was declared that power spectral density (PSD) of human high frequency EEG was composed of double Lorentzians and vanished into white level within 1kHz. Then the purpose of this study is to elucidate the “Automated Fluctuation Analysis,” which enables us to evaluate these higher frequency components and its physiological meaning especially focused on conscious level from wakefulness to sleep stage 1. Seventy-four scalp recording EEGs in twenty normal subjects were studied. In short, “Automated Fluctuation Analysis” is made of three steps: amplification of EEG signal, A/D conversion and Fast Fourier Transform by signal processor and extraction of Lorentzian parameters. PSD of high frequency EEG was displayed on log-log graph and the algorithm fit to the following Lorentzian formula were mathematically based on Brown & Dennis. S(f)=S1/ [1+(f/fc₁)²] + S2/ [1+(f/fc₂)²], where S(f) is PSD (μ V²/Hz) at each frequency (f;Hz), S1 and S2 are the plateau level or zero-frequency power of the initial and second Lorentz, and fc₁ and fc₂ are the corner or half-power frequency of the initial and second Lorentz, respectively. As results, during wakefulness the PSD of high frequency EEG activity was composed of double Lorentzian fluctuations and the power distribution of S1 value in topographical display was frontal dominant. This pattern of S1 value disappeared and S2 value became lower during sleepiness and the second Lorentz disappeared during sleep.     

轻度认知功能障碍患者工作记忆中 脑电能量及皮质联络功能的变化特征

探讨轻度认知功能障碍患者（MCI）工作记忆状态下脑电能量及皮质联络功能的变化特征。被试为从社区选取的35名轻度认知功能障碍患者和34名健康志愿者。采用简单计算回忆方法,结果发现工作记忆加工过程中会引起4.0~18.0Hz范围内功率值的改变,且MCI组高于正常对照组;MCI患者在中央、顶、颞叶的半球间相干系数均显著高于正常对照组。研究结果提示MCI患者可能存在中央、顶、颞叶皮层的功能减退,工作记忆状态下通过代偿机制仍能维持加工的有效性     

Exploring the effects of EEG signals on collision cases happening in the process of young drivers’ braking

Detecting mental states in drivers offers an opportunity to reduce accidents by triggering alerts and signaling the need for rest or renewed focus. Here we used electroencephalography (EEG) to measure brain signals in young drivers operating a driving simulator to detect mental states and predict accidents. We measured reaction times to unexpected hazardous events and correlated them with EEG signals measured from the frontal, parietal, and temporal cortices as well as the central sulcus (corresponding to motor cortex). We found that EEG signals in the relative beta (power in beta (13–30 Hz) relative to total power of the EEG (0.5–30 Hz)), alpha/delta, alpha/theta, beta/delta, beta/theta frequency bands were higher for collisions than successful collision avoidance, and that the key decision-making period is the 2nd second before braking. Importantly, a decision tree classifier trained on these neural signals predicted collision avoidance outcomes. Then based on random forest model, we extracted three critical neural signals (beta/delta_frontal, relative beta_parietal and relative beta_central Sulcus) to classify collision avoidance outcomes. Our findings suggest measuring EEG during driving may provide useful signals for enhancing driver safety.     

Extraversion,impulsiveness, and EEG alpha activity

Measures of spontaneous EEG activity in the 8–14-Hz band (alpha) obtained while subjects opened and closed their eyes on instruction were related to scores on the EPQ-E scale and scales of narrow and broad impulsiveness. Subjects with high scores on narrow impulsiveness were found to show less alpha activity than subjects with low scores. No significant relationships with alpha activity emerged for the other personality scales. It is concluded that impulsiveness rather than EPQ-E is the major correlate of differences in EEG-defined arousal.