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At least 19 recordsLinked to original sources

PubMed1977

EEG and haemodialysis. A structural survey of EEG spectral analysis, Hjorth's EEG descriptors, blood variables and psychological data.

Computerized EEG was performed in 20 patients with renal failure before and after haemodialysis (HD), applying spectral analysis and Hjorth's EEG descriptors in EEG quantification, correlation and factor analysis as statistical procedures to analyse the connections of EEG, blood variables and psychological performance. The main results were: (1) Moderate uraemic encephalopathy -- according to Kiley's (1971) standards -- was present in most of our patients, before and after HD. (2) Before HD, EEG slowing was most strongly connected with the creatinine level and EEG acceleration with hyperkalaemia, which in most cases accompanied a high urea level. (3) Significant EEG changes after HD were: decrease of percentage delta activity, increase of Hjorth's 'mobility', decrease of Hjorth's 'complexity'. (4) The theta/alpha ratio (Matousek 1968) was significantly correlated with the patient's general clinical state after HD. (5) Visual discrimination, memory and maximal tapping speed improved significantly after HD. Only Hjorth's EEG parameters were correlated with test performance in that patients with low voltage and fast EEGs did worse in visual discrimination.

Adult↗

PubMed1979

Is a man, a man, a man? (or: is an EEG, an EEG, an EEG?) some remarks on the homogeneity of "normal subjects".

Many studies involving computerized EEG analyses are based on the assumption that normal subjects constitute a homogeneous population, so that under specified conditions across-subject averaging is justified. Quite often EEG signals are processed with little or no concern for the state of the particular person from whom they are obtained. It is the purpose of this discussion to draw attention to the fact that only can normals have different EEG's one from another, but also that the same ones can display markedly different EEGs from recording session to recording session. A consequence of this situation is that there is always a large between-subject variability, and that the source of the signals needs to be carefully documented before generalizations can be made.

Adult↗

PubMed1979

The electroencephalogram (EEG) as a research tool in human behavior genetics: psychological examinations in healthy males with various inherited EEG variants. III. Interpretation of the results.

Interpretation of the results from psychological examinations of 298 probands with inherited EEG variants requires (1) critical evaluation of previous literature on psychological EEG correlates, (2) knowledge of the main concepts and experimental approaches for elucidating the basic mechanisms of EEG rhythms, (3) discussion of previous attempts to link psychological variation in human populations with corresponding variation in brain function, and (4) interpretation of results from considerations at these three levels with the data from our own study. At the first level (previous psychological studies), comparison with Schmettau's study proved to be especially revealing: Her conclusions about personality correlates with high alpha-index and with "flat" EEGs were very similar to ours with the monotonous alpha- (R) and low-voltage (N) EEGs, respectively. Her EEG type with high beta-index overlaps with our beta-diffuse (BD) type; a tendency to psychasthenia and low resistance to stress is less obvious in our group, but is expressed indirectly by reduced speed and accuracy in tests requiring attentiveness and persistence. The correlation between alpha-frequency and intelligence found in other studies was confirmed by the especially high intelligence scores of our group with occipital fast alpha-variants (BO). At the second and third levels of the discussion (EEG mechanisms; neurophysiological theories), the cooperation of cerebral cortex (EEG battery), thalamus (pacemaker), and ARAS (tonic arousal) is discussed, and the personality typologies of Eysenck and Claridge are mentioned. From this and other evidence, the following hypotheses are discussed: 1) The personality profiles of the R group are influenced by high activity and efficiency of the thalamic alpha-pacemaker(s), which leads to a high degree of modulation, selection, and amplification of afferent stimuli. 2) In the countertype of this EEG variant, the N EEG, a low modulation and amplification by the thalamic alpha-pacemaker is assumed. This leads to relatively low intensity of feeling and to low spontaneous activity, but to faster information processing. Combined with an increased level of tonic arousal in the ARAS, it may cause certain 'neurotic' complaints (our low-voltage borderline (NG) group). 3) The EEG with diffuse beta-waves (BD) is caused by a high level of tonic arousal in the ARAS, which tends to distrub the thalamocortical circuit. This leads to reduced stress resistance and to impairment of intellectual functions, especially space perception. Due to limited evidence, the next two hypotheses are advanced only tentatively: 4) alpha-rhythm with very high frequency 16--19 c/s) leads to improvement of information processing and, hence, to high intellectual performance and motor dexterity. 5) Probands with frontoprecentral beta-groups (BG) show no psychological signs of increased tonic arousal; therefore, these beta-groups are caused not by increased tonic arousal of the ARAS, but by a genetic variant of a thalamic subsystem.

Adult↗

PubMed1979

The electroencephalogram (EEG) as a research tool in human behavior genetics: psychological examinations in healthy males with various inherited EEG variants. I. Rationale of the study. Material. Methods. Heritability of test parameters.

In the first section of this paper, various research designs in human behavior genetics are compared. In this context, the commonly used concept of biometric genetics is critically evaluated from the point of view of science theory. It is contrasted with the Mendelian gene concept, which, in principle, leads to a much deeper theoretical understanding by offering clues for basic mechanisms. To explore this advantage fully, a research strategy is needed that first looks for genetic variability in a physiological parameter of possible importance for human behavior and then tries to explore the influence of this parameter on the function of the human brain and on behavior. If possible, this genetic parameter should be selected in a way that inferences as to the mechanism of its influence on behavior become feasible. Such genetic variability is provided by the hereditary variants of the normal EEG discovered by earlier work (cf. Vogel, 1970). In the following section, a research program on 298 adult healthy males, most of them soldiers, with various inherited EEG variants is described. Apart from controls with inconspicuous EEGs, this material comprises probands with the following EEG variants: low-voltage (N); low-voltage borderline (NG); monotonous alpha-waves (R); occipital fast alpha-variants (BO); fronto-precentral beta-groups (BG), and diffuse beta-waves (BD). In addition to an EEG examination, the probands were examined with various test methods measuring intelligence (IST; LPS; Raven); working speed and concentration (d-2; KLT); personal attitudes (MMPI; 16PF; RKS); and sensory and motor abilities (flicker fusion; tachistoscopy; reaction time to optic, acoustic and combined stimuli; two-hand dexterity; pursuit rotor; tapping). In a supplementary twin study on 52 male adult twin pairs (26 MZ, 26 DZ), heritabilities were determined for the test scores included in the main study. For most test scores, heritabilities are relatively low; the data are compared with those from the literature. We conclude that the test methods utilized in the main study (on EEG variants) are expected to demonstrate at the most a small to moderate correlation of the EEGs with psychological phenotypes as defined by test examinations, even if a major part of the genetic variability underlying these phenotypes would be due to differences in brain physiology that could be revealed by EEG variation.

Adult↗

PubMed1979

Hippocampal EEG and behaviour in dog. I. Hippocampal EEG correlates of gross motor behaviour.

It was shown that rewarding spectral shifts (i.e. increase in amplitude or peak frequency of the hippocampal EEG) causes a solitary dog to show increased motor behaviour. Rewarded spectral shifts concurred with a variety of behavioural transitions. It was found that statistically significant modulations occur in the spectral properties of the hippocampal EEG correlated with: (1) the transition from walking to standing; (2) the transition from standing while eating to walking away from the food dish; (3) the increase in speed of a walking dog, caused by rewarding the animal; and with (4) each head movement in a learned series of head movements. Thus behavioural transitions to a more active state are accompanied by an increase of amplitude, frequency and rhythmicity in the theta band of the hippocampal EEG; behavioural transitions to a less active state show the inverse relationship with the hippocampal EEG. A close relationship between modulations of the dog's hippocampal EEG activity and elementary motor acts is stressed. The hypothesis is put forward that the spectral properties of the hippocampal EEG reflect the degree to which a number of motor and sensory structures in the limbic midbrain and brain stem are active.

Animals↗

PubMed1979

Prognostic value of EEG in acute vascular aphasia: a long term clinical-EEG study of 53 patients.

A group of 53 patients rendered acutely aphasic by occlusive cerebrovascular disease were studied by serial EEG's, repeated neurologic examinations and speech evaluations (Porch Index of Communicative Ability) over a period of eight to twenty-four months, in order to correlate EEG findings with the degree of language disorder and prognosis for language recovery. Normal and mildly abnormal EEG's, posterior slow foci, focal slowing of semirhythmic type and higher alpha frequencies over the intact hemisphere correlated with good language recovery. In the majority of the patients, the curves of "EEG Improvement" and "Language Recovery" closely paralleled each other. These data indicate that the EEG is of prognostic value as to recovery from aphasia in patients suffering from acute occlusive cerebrovascular disease. Despite the advent of newer diagnostic tests, such as CAT scan, which has established its value in evaluation of the anatomy of aphasia, (9) EEG remains to be useful as a tool that could predict the outcome of aphasia in stroke patients.

Adult↗

PubMed1978

[Centralized system for EEG-diagnosis and EEG-monitoring in a neurologic intensive care unit (author's transl)].

A centralized EEG system installed in a neurologic intensive care unit is described. It is the first step to a computerized EEG monitoring which on the basis of conventional EEG recordings already permits a "brain monitoring" to some extent. It consists of a system for total EEG diagnosis which is connected with a central EEG laboratory via long-distance transmission lines, and of a system for EEG-monitoring which is part of the general beside monitor system. The possibilities of this system are demonstrated in monitoring of patients with epileptic seizures.

Aged↗

PubMed1975

An EEG simulator-a means of objective clinical interpretation of EEG.

In 1969 Zetterberg presented a method for describing the spectral properties of an EEG signal, starting from the assumption that the signal is essentially stationary during the analysis epoch. The method involves determination of the parameters for a model consisting of a lenear filter with the ability to produce a signal with the same spectral properties as the EEG signal. Zetterberg and Ahlin described in 1975 an analogue simulator based on this model theory. With this simulator it is possible to reproduce practically all types of stationary, as well as a number of non-stationary, EEG signals. We have used this simulator to demonstrate in an illustrative manner the relation between the properties of a signal in the spectral domain and in the time domain. We have also endeavoured to anser the question: if one starts from the frequency spectrum, what does the EEG signal corresponding to this spectrum look like? We also draw attention to the usefulness of the simulator in connection with training and as an instrument for testing computer and other systems of EEG analysis.

Computers↗

PubMed1979

Hippocampal EEG and behaviour in dog. III. Hippocampal EEG correlates of stimulus-response tasks and of sexual behaviour.

A dog was trained to perform a spatial sound discrimination. The hippocampal EEG correlates and the movement correlates of correct trials were compared with those of incorrect trials and of 'pressings in between'. Correct and wrong responses on a place learning task were compared both with respect to the hippocampal EEG correlates and to the motor behaviour. Where significant differences in EEG correlates were found, the motor behaviour differed significantly as well. The same was found for 2 behavioral states with different motor behavioural qualities which occurred during copulation. The data support the hypothesis that the spectral properties of the hippocampal EEG reflect in a predictable but non-specific way the intensity of motor behaviour. They question the postulated correlations between hippocampal EEG and 'internal processes', on the ground that unambiguous experimental verification of such hypothesis appears to be very difficult.

Animals↗

PubMed1977

Adaptive segmentation of EEG records: a new approach to automatic EEG analysis.

The first step in a procedure for automatic EEG analysis is to compress the incoming data into a manageable format while preserving the essential diagnostic information. In our approach we mimic the visual procedure of looking through the record for segments and events of particular interest. We assume that the EEG is composed of roughly stationary segments of variable length, possibly superposed by sharp transients. By using an autoregressive model we have developed a procedure to detect the segment boundaries and locate transients, and to represent the information in the segments in terms of a set of parameters specifying their power spectra. In this way, the time structure as well as the frequency content of the signal is preserved. Examples of segmentation and transient detection are shown for several EEG signals, and the quality of the representation is demonstrated by simulating the original signal from the parameters. Possible applications to practical EEG analysis are discussed.

Adult↗

PubMed1979

Hippocampal EEG and behaviour in dog. II. Hippocampal EEG correlates with elementary motor acts.

A positive correlation has been shown between the speed of forced stepping on a conveyor belt and the amplitude and frequency of the concomitant hippocampal EEG. Significant modulation in the spectral properties of the dog's hippocampal EEG has been found in relation to 3 elementary motor acts: stepping, respiratory movements and a reflex movement in reaction to linear acceleration of the animal. The findings support the idea that within a certain experimental situation the hippocampal EEG reflects the intensity of motor behaviour in a non-specific but predictable way. However, some experimental results indicate that sensory inputs may modulate the hippocampal EEG as well.

Animals↗

PubMed1977

EEG operant conditioning in a monkey model: II. EEG spectral analysis.

EEG power spectral analysis was studied from 14 (alumina-gel) chronically epileptic, undrugged monkeys during an EEG operant conditioning experiment. The composite profile of the average epileptic monkey shows the majority of power to be below 10 Hz. Because of the large variance in the data, no significant changes in the EEG power spectra could be detected as a function of conditioning. The possible reasons for this large variance are discussed. Hypothesis from previous human "biofeedback" studies would allow the prediction that those frequencies corresponding to the mu and sensory-motor-rhythm should negatively covary with seizure frequency. Data from this study did not support such assertions. The method of using spectral analysis for quantifying changes in the EEG which covary with operant conditioning is evaluated.

Animals↗

PubMed1976

[Psychophysiological studies of EEG, operational performance and the dynamics of vigilance regulation. I. The EEG during performance of Brickenkamp's attention-concentration test (test d 2) (author's transl)].

During the performance of the d 2 test developed by Brickenkamp (standardized test of attention and concentration), occipital EEG activity was registered telemetrically in 10 male students aged 25 to 32 years. Simultaneously, the pencil markings performed by the subjects, indicating the time course of their pattern recognition and discrimination, were recorded by means of a piezo-electrical transducer. The EEG behavior during test performance was evaluated by serial spectral analysis. The analysis of the EEG parameters derived from it (total power, absolute and relative alpha-power) showed that there is a relationship between these EEG measures reflecting the regulation of cortical vigilance and the error rate in the concentration test. While subjects with low error rate present a heightening of cortical arousal focused in the right occipital area, subjects with higher error rate tend to have a higher degree of general cortical activation.

Adult↗

PubMed1979

Combined dynamics of EEG and evoked potentials. I. Studies of simultaneously recorded EEG-EPograms in the auditory pathway, reticular formation, and hippocampus of the cat brain during the waking stage.

This study is carried out on single (not averaged) recordings combining the spontaneous activity preceding the stimulus onset and the EP recorded upon acoustical stimulation. These recordings, which we call EEG-EPograms, are measured simultaneously from different subdural brain structures, such as the auditory cortex, medial geniculate nucleus, inferior colliculus, reticular formation and the hippocampus of awake cats. Using a combined analysis procedure (C.A.P.), the relevant frequency components of spontaneous EEG and EPs, recorded simultaneously from these brain nuclei, are analyzed according to the consistent selectivity bands depicted by the determined amplitude-frequency characteristics. These analyses provide us the following information: (1) there is an important congruency in the time courses of simultaneous response components in common frequency bands, especially in the alpha and beta frequency ranges; (2) there exist significant coupling and synchrony between the evoked amplitude enhancements in the simultaneously recorded single response components; (3) the inter-nuclei coherency in the brain's electrical activity is enormously increased upon stimulation; (4) the evoked response magnitude can be predicted, with reasonable accuracy, from the spontaneous activity preceding the stimulation. The strong dependence of the response magnitude on the stimulus-preceding EEG is explained by means of a model network consisting of a population of relaxation oscillators, which can be brought to different states of synchrony and asynchrony. Some suggestions and comments are also made for investigators working toward theories of signal transmission in the brain.

Animals↗

PubMed1979

The electroencephalogram (EEG) as a research tool in human behavior genetics: psychological examinations in healthy males with various inherited EEG variants. II. Results.

The results of psychological examinations on 298 adult male probands with various inherited EEG variants are described. They may be summarized as follows: 1) The low-voltage (N) group scored high in intelligence tests, especially in spatial orientation. Personality scores revealed this group as 'normal', extravert, group-dependent, and not very energetic. 2) The borderline low-voltage (NG) group showed slight weakness in abstract thinking, short-time memory, and motor skills and a relatively strong tendency to have 'neurotic' complaints. Reaction time and motor skills were poor. 3) The occipital fast alpha-variants (BO) group performed very well in tests of abstract thinking and motor skills. 4) The monotonous alpha (R) group showed average performance in most intelligence scores but above-average in short-time memory and in precision under stress conditions. Personality scores indicated high spontaneous activity and toughmindedness. 5) The BG (fronto-precentral beta-group) category showed very low MMPI scores, indicating little neurotic tendency. Intelligence could be above average. 6) The diffuse beta (BD) group scored low in intelligence tests, especially in spatial orientation, and had a high error rate in tests measuring concentration and precision. Most differences were relatively small; the whole range of test scores could be found in all EEG groups.

Adult↗

PubMed1979

Combined dynamics of EEG and evoked potentials. II. Studies of simultaneously recorded EEG-EPograms in the auditory pathway, reticular formation, and hippocampus of the cat brain during sleep.

This study is carried out on single (not averaged) recordings combining the spontaneous activity preceding the stimulus onset and the EP recorded upon acoustical stimulation. These recordings, which we call EEG-EPograms, are measured simultaneously from different subdural structures, such as the auditory cortex, medial geniculate nucleus, inferior colliculus, reticular formation and the hippocampus of the cat brain during the slow wave sleep stage. Using a combined analysis procedure (C.A.P.), the relevant frequency components of spontaneous EEG and EPs, recorded simultaneously from these brain nuclei, are analyzed according to the consistent selectivity bands depicted by the determined amplitude-frequency characteristics for the SWS-stage. In parallel with the results which we obtained for the waking stage, these analyses provide also the following information: (1) there is an important congruency in the time courses of simultaneous response components in common frequency bands, especially in the alpha and beta frequency ranges; (2) there exist significant coupling and synchrony between the evoked amplitude enhancements in the simultaneously recorded single response components; (3) the inter-nuclei coherency in the brain's electrical activity is enormously increased upon stimulation;(4) the evoked response magnitude can be predicted, with reasonable accuracy, from the spontaneous activity preceding the stimulus. All these findings are discussed with reference to those obtained for the waking stage.

Animals↗

PubMed1979

[Spectral analytical study on the developmental properties of EEG in children: variability of EEG in normal and mentally retarded children (author's transl)].

The present study aimed at clarifying the characteristics of variability of the resting arousal EEGs in normal and mentally retarded children. Their ages ranged from 3 to 15 years in 58 normal and from 7 to 18 in 63 retarded. The EEG was recorded monopolarly from six regions of the scalp. The data analysed by a multipurpose digital computer comprised auto-power spectra and a coefficient of variation of power at each frequency. The variability of power at peak within the theta frequency band in both groups of children showed a notably higher value as compared with other frequency bands in all regions. We discussed some of the problems of treating this variability of power as a general characteristic of theta waves or as a developmental one.

Adolescent↗

PubMed1978

[The mathematical rationale for the clinical EEG-frequency-bands. 1. Factor analysis with EEG-power estimations for determining frequency bands].

In order to determine whether the clinically used frequency bands of the EEG can also be obtained by a mathematical system we did a factor analysis with 480 EEG recordings, 5 minutes each, in 60 healthy male volunteers. A power spectrum analysis was done and 57 frequency bands between 1.5 and 30.0 Hz in a half Hz steps were calculated. The factor structure obtained made the following frequency bands (Hz) reasonable: deltaF = 1.5 - 6.0, thetaF = 6.0 - 8.5, alpha1F = 8.5 - 10.5, alpha2F = 10.5 - 12.5, beta1F = 12.5 - 18.5, beta2F = 18.2 - 21.0, beta3F = 21.0 - 30.0. Except for alpha1F all other 6 frequency bands were represented by one general factor with the complexity 1. The variance of the alpha1F band is explained by several of the 6 factors. The clinically known and the by factor analysis obtained frequency bands in the beta-range are similar. The clinically alpha-band is subdivided into two frequency bands alpha1F and alpha2F by the factor analysis. The clinically known border line between delta- and theta-band of 3.5 Hz cannot be found by factor analysis.

Adult↗