Genetic determination of the human EEG

Summary In this article, we have discussed recent progress in quantifying the genetically determined component of the resting EEG. This progress has been made possible in particular by the application of advanced information processing techniques such as supervised learning, and the development of a problem-oriented similarity concept. Our work aimed at modeling previous findings regarding the distinct individuality of human brain-wave patterns, the high similarity between the EEGs of monozygotic twins, and the average within-pair similarity of dizygotic twins. Thus, we had three objectives: First, we wanted to improve the quantification of EEG characteristics with respect to reproducibility and specificity by means of adaptive procedures and repeated measurements. Second, we wanted to compare the typical within-subject EEG similarity with the typical within-pair EEG similarity of monozygotic and dizygotic twins brought up together. Finally, we were interested in the degree to which environmental factors affect the characteristics of human brain-wave patterns. Our investigations were based on the empirical data derived from five different populations: (1) 81 healthy subjects, (2) 24 pairs of monozygotic twins brought up together, (3) 25 pairs of dizygotic twins brought up together, (4) 28 pairs of monozygotic twins reared apart, and (5) 21 pairs of dizygotic twins reared apart. Following our similarity conception, repeated measurements on the set of 81 individuals were used as design samples, and new registrations from the same individuals taken 14 days later were referred to as test samples in order to develop the appropriate method and to determine all required calibration parameters. This specific approach allowed us to construct EEG spectral patterns which, with a specificity and reproductibility of>90% each, largely met the requirements of genetic EEG studies. Hence, we were able systematically to investigate the within-pair EEG similarity of our twin samples. Our results provided ample evidence that the individual characteristics of the resting EEG are primarily determined by genetic factors: (1) There exists an almost perfect one-to-one mapping between each individual and his EEG; (2) monozygotic twins proved, with respect to their resting EEGs, to be only slightly less like one another (if there is any difference at all) than each person is to himself over time; (3) the average within-pair EEG similarity estimated from a sufficiently representative sample of dizygotic twins is significantly above the inter-individual EEG similarity between unrelated persons (this finding holds true for both samples of dizygotic twins brought up together and reared apart, and there is also no statistically significant difference in the resting EEG between these two samples) and, (4) the EEGs of monozygotic twins reared apart are obviously as similar to each other as are the EEGs of the same person over time, and there is no statistically significant difference in the resting EEG between the two populations of monozygotic twins brought up together and monozygotic zygotic twins reared apart.     

Dynamic processes in the human EEG

The possible mechanisms which determine the temporal dynamics of discrete narrow-band spectral components of human EEG recorded by a single electrode in the state of rest were analyzed. The dynamics of short-segment spectra was observed by application of Fast Fourier Transform (FFT) to 5-s EEG epochs successively shifted by 0.32 s. For each subject the matrices were formed and presented in a graphic mode. Matrix rows represented the number of points in each short-segment spectrum, and the columns represented the number of short-segment spectra. The columns reflect the amplitude dynamics of a given frequency, and power transition between the columns reflects the frequency dynamics. The most common type of the amplitude dynamics consisted in short (2-8 s) periods of stable activity of the discrete spectral components replaced by symmetrical bifurcation or confluence of spectral peaks. The obtained results suggest by the presence of both additive and multiplicative mechanisms of oscillatory interactions in the EEG. More detailed analysis of the amplitude-modulated EEG processes is provided by application of some additive features of the FFT to both EEG and computer-simulated signals.     

A double-blind investigation of the relationship between seizure activity and the sleep EEG following EEG biofeedback training

The sleep EEGs of eight medically refractory epileptic patients were examined as part of a double-blind, ABA crossover study designed to determine the effectiveness of EEG biofeedback for the control of seizures. The patients were initially reinforced for one of three EEG criteria recorded from electrodes placed over sensorimotor cortex: (a) suppression of 3- to 7-Hz activity, (b) enhancement of 12- to 15-Hz activity, or (c) simultaneous suppression of 3- to 7-Hz and enhancement of 11- to 19-Hz activity. Reinforcement contingencies were reversed during the second or B phase, and then reinstated in their original form during the final A′ phase. All-night polysomnographic recordings were obtained at the end of each conditioning phase and were subjected to both visual and computer-based power spectral analyses. Four of the patients showed changes in their nocturnal paroxysmal activity that were either partially or totally consistent with the ABA′ contingencies of the study. The spectral data proved difficult to interpret, though two trends emerged from the analyses. Decreases in nocturnal 4- to 7-Hz activity were correlated with decreases in seizure activity, and increases in 8- to 11-Hz activity were correlated with decreases in seizure activity. These findings were shown to strengthen the hypothesis that EEG biofeedback may produce changes in the sleep EEG that are related to seizure incidence.     

复杂度脑电地形图研究

脑电地形图是近年脑电分析的热点之一。通过对各种复杂度算法的分析得出,近似熵由于所需要的时间序列长度较短,大大减少了脑电非平稳性所带来的困难,且无需粗粒化,在对生物医学信号的复杂度分析中有其一定的优点,采用近似熵对多道脑电信号的复杂度运算结果,通过空间插值,构建复杂性动态脑地形图,以便于观察大脑各部ＥＥＧ信号复杂度在同一时刻的相对强弱关系和这种关系随时间的变化。并通过对一些脑疾病患者脑电数据的分析,     

Concerning the amplitude modulation of the human EEG

Amplitude-modulated processes can be formally presented as a product of two or more sinusoids. This makes it possible to study them by means of analysis of multiplicative phenomena using the Fast Fourier Transform (FFT). To assess the contribution of amplitude EEG modulation to the dynamic of electrical activity of the human brain, the results of the FFT of simulated signals obtained by multiplication of oscillatory processes with different parameters were compared with the results of the FFT of a single EEG recording from a subject at rest. We studied the temporal dynamics of spectral components calculated with different spectral resolution under similar conditions for real and simulated signals. An attempt was made to analyze and interpret the amplitude-modulated EEG processes using the additive properties of the FTT. It was shown that processes of amplitude modulation are present in electrical brain activity and determine the synchronism of changes in time in the majority of frequency components of the EEG spectrum. The presence of the amplitude modulation in bioelectrical processes is of a fundamental nature, since it is a direct reflection of the control, synchronization, regulation, and intersystem interaction in the nervous and other body systems. The study of this modulation gives a clue to the mechanisms of these processes.     

Topographic EEG mapping of the relaxation response

The purpose of this study was to assess the central nervous system effects of the relaxation response (RR) in novice subjects using a controlled, within-subjects design and topographic EEG mapping as the dependent measure. Twenty subjects listened to a RR and control audiotape presented in a counterbalanced order while EEG was recorded from 14 scalp locations. TheRR condition produced greater (p<.0164) reductions in frontal EEG beta activity relative to the control condition. No significant differences were observed for any other frequency band or scalp region. These findings suggest that elicitation of the RR produces significant reductions in cortical activation in anterior brain regions in novice subjects.     

EEG and implanted sources in the brain

Localisation procedures are based on models of the EEG that are relatively simple. The models are based on assumptions and choices of parameters that can be mistaken. Thus, it is crucial to validate the localisation procedures used in EEG. One of the options is to use the data obtained with electrodes that are implanted within the brain of an epileptic patient as part of the pre-surgical evaluation. When one of two neighbouring electrodes is used as a current source and the other as a current sink this can be regarded as a current dipole. The current injected has to be below the threshold for activation of cells. The position of this dipole can be deduced from magnetic resonance or X-ray images. The current dipole gives rise to a potential distribution at the scalp that can be measured by EEG. The measurements can be compared with the potential distribution that is calculated in a forward computation. Another method is to use the measured potential at the scalp to localize the source and to compare the result with the actual position of the dipole. In this paper the measured potential distributions at the scalp due to implanted dipoles were used to evaluate different volume conductor models. Since intracerebral and subdural electrodes were introduced through trephine holes over the fronto-central areas, and the diameter of the holes was rather large, approximately 23 mm, special effort was put into modelling the skull. Two important assumptions could be validated in this study: the electric currents within the head are Ohmic and a dipole can be used to model the induced electric activity of pairs of contacts on subdural electrodes or intra cerebral electrodes.     

Alpha-rhythm of the EEG in directed attention

Degree of manifestation and synchronization of rhythmic alpha-range components in various cortical areas was studied in healthy adult subjects in conditions of controlled computer experiment by spectral-correlation method of EEG analysis during directed attention previous to discrimination of tactile, auditory and visual stimuli. The obtained results show that in preparation for discrimination of heteromodal stimuli, specific reconstructions take place of alpha-range electrical activity determined by signal modality. These changes are expressed in a local increase of the degree of synchronization of alpha oscillations in those projection and associative brain areas which are connected with the analysis of the given stimuli. Functional significance of these reconstructions is seen in the fact that they are significantly more expressed at correct recognition. A hypothesis is suggested about participation of the alpha-range in neurophysiological mechanisms of directed attention.     

Combinatorial relations in the EEG spectrum]

The geometric mean frequency of any EEG wave divides its frequency band B into sub-bands b and s. For the wave beta the values s, b and B are the subsequent elements of the geometric progression with denominator equals to the invariant of the gold section. A hypothesis was proposed that all the EEG waves were described by the system SG of the recurrence equations. This system was derived by the generalization of the Fibonacci generating function. Theoretical invariants Ilambda of the system and experimental ratios b/s were found to coincide with the quadratic mean error equals to 1%. The system SG predicts the existence of the EEG waves, rho and sigma (55-118, 118-225 cycles per sec.), which have not yet been discovered experimentally.     

The cortical EEG in the acallosal mouse

The congenital absence of the corpus callosum has recently been found to occur among some mice of the ddN strain in our laboratory. Morphologically, the absence of corpus callosum was classified into two types. One was complete agenesis of corpus callosum, and the other revealed partial agenesis (genu or splenium, or both). In this experiment, the differences of cortical EEG spectral characteristics were studied on the normal, hypogenesis and acallosal mice. A total of 75 male and female adult mice were used. Under light ether anesthesia, five stainless steel electrodes (0.29 mm) were implanted stereotaxically in the bilateral cerebral cortex and cerebellum at a depth of 1.0 mm. After one week recovery period, the correlations of EEG of five combinations, such as homotopic anterior vs. posterior, left vs. right hemispheres, crossed contralateral, and homotopic anterior and posterior to the reference electrode, were analysed with a signal processor. In the complete acallosal mice (n = 11), the correlation coefficients were significantly lower (p less than 0.05), in the crossed contralateral, left vs. right hemispheres, and homotopic posterior to reference. In the hypogenesis of corpus callosum (n = 7), however, they were no significant differences in the correlation compared with normal mice (n = 57). At the end of experiment, the brain was removed and fixed with 10% formalin, then it was cut in half along the midsagittal plane. The midsagittal section was used to examine an outline of the corpus callosum.