Introduction: There is substantial lack of well-designed functional electrophysiological studies with respect to pathophysiology and prognosis after cerebral ischaemia despite increasing progress in neuroimaging. Methods: We prospectively investigated 25 consecutive patients with acute first-ever supratentorial ischaemic stroke and no history of epilepsy. 24h-EEG monitoring was started within 12 hours after the onset of symptoms. The neurological deficit was assessed by NIH Stroke Scale (NIHSS) and Barthel Index (BI) during EEG recording and after I year. Results: Blinded EEG evaluation revealed 3 hierarchical classes: focal slowing (n = 9, group C), focal high voltage discharges (n = 10, group B) and epileptiform activity (n = 6, group A). Temporo-spatial EEG evolution was illustrated in reproducible time series and thus allowed a refined analysis of the underlying pathophysiology. Slowing-down of the background activity, occurrence of contralateral potentials and rhythmic focal slowing-down seemed to correlate with a higher incidence of high-voltage discharges and epileptiform activity. The EEG groups differed significantly (p < 0.0001) in NIHSS BI and in the occurrence of seizures. All patients of group C had a good outcome (NIHSS < 10, BI > 60) and no one developed seizures (predictive value [pv] - 1: 95% confidence interval [Cl] 0,72 - 1). In contrast all patients of group A had a poor outcome (NIHSS > 20, BI < 20 or death: PV 1, Cl 0,61 - 1) and 5 of them developed seizures (PV 0,83; Cl 0,36 - 1). Patients with epileptic seizures had a significant higher mortality (p < 0.025) Conclusions: Our data underline the importance of early post-ischaemic EEG recording both for understanding pathophysiological mechanisms of post-ischaemic seizures and the prognosis of acute stroke.

Objective: To include a larger number of tetraplegics than in previous studies, in order to more reliably characterize the pathogenesis and predisposing factors of sleep apnea in tetraplegia. Methods: Sleep breathing data and oxymetric values were investigated in 50 randomly selected tetraplegic patients and discussed in context with age, gender, BMI, neck circumference, type and height of lesion, time after injury, spirometric values and medication. A non-validated short questionnaire on daytime complaints was added. Results: Thirty-one patients out of 50 had an RDI ⩾15, defined as sleep disordered breathing (SDB); 24 of them combined with an apnea index of 5 or more, these cases were diagnosed as sleep apnea syndrome (SAS). SAS was apparent in 55% and 20% of the studied men and women, respectively. Regression analyses showed no significant correlation between RDI and lesion level, ASIA impairment scale or spirometric values. In contrast, a significant correlation between RDI and age, BMI, neck circumference and time after injury could be shown. Kruskal-Wallis test for dichotomous non-parametric factors, such as gender, cardiac medication and daytime complaints, showed significant differences with regard to RDI. In contrast to able-bodied people with SAS, daytime complaints were only present in tetraplegic patients with severe pathology (RDI>40). Conclusion: Incidence of SAS is high in tetraplegia, particularly in older male patients with large neck circumference, long standing spinal cord injury and under cardiac medication. As tetraplegics with RDI between 15 and 40 reported no daytime complaints and often have normal BMI, these tetraplegics are not clinically suspicious for SAS. The increased use of cardiac medication in tetraplegics with SAS may implicate a link between SAS and cardiovascular morbidity, one of the leading causes of death in tetraplegia.

Fifteen patients aged between 26 and 55 years with the acquired immunodeficiency syndrome (AIDS) and various cerebral manifestations of the disease underwent an all-night sleep electroencephalogram (EEG) registration. The recordings of 15 age-matched volunteers were examined as controls. Sleep stages were determined visually and the following spectral analysis was based on corresponding artifact-free 40-second periods. The sampling rate was 64 second-1, the spectral resolution was 0.25 Hz and the frequency ranged from 0.25-24 Hz. The power density spectra of eight EEG derivations (left and right frontopolar, frontal, central and occipital; reference montage to the ipsilateral Cb electrodes) and the coherence spectra of interhemispheric (interfrontal, interoccipital) and intrahemispheric (frontooccipital, left and right) channel pairs were computed. The power density of the patients in the 11.5-13-Hz frequency range of nonrapid eye movement (NREM) sleep was considerably lower than that of the controls (p < 0.05 and p < 0.01 at left and right frontal derivations, two-tailed Mann-Whitney U test). The power density of rapid eye movement (REM) sleep showed no consistent differences between the two groups. The interfrontal coherence of the whole frequency range below 12 Hz was markedly lower in the patient group. This applied to NREM sleep and also to REM sleep (p < 0.01 and p < 0.001 for different frequency bands between 1 and 12 Hz in NREM and REM sleep). Possible relations to clinical features are discussed.

A term like “alpha activity in sleep” seems to be contradictory. Since H. Berger’s first publication (1929), a rhythmically organized activity in the alpha frequency range is usually associated with a relaxed waking state, and this explicitly serves as a criterion for the definition of the posterior alpha background rhythm (IFSECN, 1974). The designation of a frequency band, however, is purely descriptive and should not imply a specific functional meaning, state of vigilance, or clinical correlation. In this chapter, therefore, the term “alpha” refers only to “in the alpha frequency range,” and the particular activity is specified by indicating the state during which it is recorded. Non-rapid eye movement (NREM) alpha activity is equivalent to rhythmical activity in the alpha frequency range recorded during physiological NREM sleep.

All night sleep deprivation prior to an EEG registration causes some inconvenience not only to the organization of the EEG department but presents a burden on the patients as well as their family members, and for these reasons is not suitable to be frequently employed as a routine procedure. As an alternative, we performed short-term sleep recordings in the early afternoon following a partial sleep deprivation of the patients during the preceding night. This method was well accepted by the patients and their family. Our only goal was to shorten the total time of night sleep using the following guideline: for very small children 22.00-06.00; for 4-14-year-old patients 24.00-06.00; and for patients older than that 01.00-06.00. 79.9%, out of 719 patients (573) who had been given the above instructions subsequently showed sleep patterns in their EEG. Additionally we had to administer an oral dose of promazine to only 67 patients. However, for the most part, patients showed only light sleep stages: 114 patients only reached sleep stage 1; 323 patients sleep stage 2; 88 patients sleep stage 3; and 48 patients sleep stage 4. As expected, REM sleep was never recorded. Nonetheless, in 32 out of 146 patients who were tired but unable to fall asleep, epileptic patterns could be provoked. In 636 patients, the EEG-recording after sleep reduction was ordered because of a suspected seizure disorder; in the remaining patients it was initiated solely because of sharp components in the routine-EEG. In 341 (53.6%) of the patients with suspected epilepsy, electroencephalographic activity indicative of a seizure disorder was activated. Such epileptic patterns were recorded almost exclusively in stages of waking, 1 and 2. Only in one out of the 124 patients who reached sleep stages 3 and 4 epileptic patterns were not seen until deep sleep was entered. We observed 2/s, 3/s and 6/s spike-and-wave complexes, sharp waves, spikes, polyspikes, groups containing remarkably sharp components and so called sharp vertex grapho-elements. Patients with suspected seizure disorders frequently show grapho-elements which can be interpreted as the expression of a disposition for epilepsy. These sharp vertex elements were evident in 54 out of 719 short term sleep recordings, more often in children than in adults. 49 times they coincided with typical epileptic discharges such as sharp waves, spikes or spike-and-waves in the same recording.

The evaluation of EEG-patterns is usually accomplished by visual analysis. Nowadays however, even personal computers are fast enough for an efficient pattern recognition of EEG signals. Using sleep spindles and K-complexes as examples, our aim was to demonstrate how patterns can be detected in an EEG signal with a high degree of accuracy. Furthermore, recognition of K-complexes has been improved by applying an additional "adaptive algorithm" allowing individual adjustments to the signal's form and amplitude.

Spectral analysis was performed to study the response of various EEG sleep activities to a modification of GABAergic sleep regulation by flunitrazepam. We observed sleep stage- and sleep cycle-dependent differences in the topographic distribution of the reactions. An increase in power density was found in the frontal regions for the alpha 2 and sigma 1 frequency band whereas a decrease in power density was emphasized in the posterior regions for the delta and alpha 1 frequency band. These topographic differences might be related to the regional distribution of benzodiazepine receptor subtypes.

The evaluation of EEG-patterns is usually accomplished by visual analysis. Nowadays however, even personal computers are fast enough for an efficient pattern recognition of EEG signals. Using sleep spindles and K-complexes as examples, our aim was to demonstrate how patterns can be detected in an EEG signal with a high degree of accuracy. Furthermore, recognition of K-complexes has been improved by applying an additional „adaptive algorithm”, allowing individual adjustments to the signal's form and amplitude.

The evaluation of EEG-patterns is usually accomplished by visual analysis. Nowadays however, even personal computers are fast enough for an efficient pattern recognition of EEG signals. Using sleep spindles and K-complexes as examples, our aim was to demonstrate how patterns can be detected in an EEG signal with a high degree of accuracy. Furthermore, recognition of K-complexes has been improved by applying an additional "adaptive algorithm", allowing individual adjustments to the signal's form and amplitude.

To investigate the temporal organization of EEG sleep activity in the second and minute ranges we developed a method which, based on Fourier transformation, allows the presentation of periodic oscillations of spectral power and coherence. The application of this method is demonstrated in 3 subjects with different types of alpha activity during sleep: (a) alpha-sleep pattern (a physiological variant of NREM sleep activity); (b) abnormally increased arousal alpha activity. The results show that differences in the temporal organization of these alpha activities can be determined with the following parameters: period length, duration of sequences with periodic activity, number and rate of these sequences, and proportion of periodicities generated simultaneously in the left and right hemispheres. The physiologically modulated periodicities of the alpha-sleep pattern are contrary to a stereotyped 40–60 sec periodicity of abnormal arousal alpha activity. Such abnormal periodicity corresponds to periodicities occurring in association with other sleep disturbances, such as sleep apnea or periodic movements in sleep. Periodicity analysis gives additional criteria for a more refined evaluation of normal as well as abnormal sleep structure.

In ailnight sleep recordings usually 12 to 16 channel electroencephalographs are used to record the electrical activity of the brain. A detailed analysis of EEG sleep activity, however, requires the inclusion of at least the 19 electrodes placed according to the international 10-20 system in order to compare the variations of the activities in different brain areas. In addition polygraphic parameters such as ECG, respiration and actogram, to mention just a few, have to be recorded depending on the type of study. Therefore the number of recording channels has to be increased for a complete polygraphic investigation. We developed a 32 channel unit with a personal computer and corresponding hardware interfaces allowing the continuous digitalization of up to 32 bioelectrical signals throughout the whole night (8 hours). The recorded data can be presented graphically and evaluated according to the usual methods such as power spectrum, coherence and periodicity analysis.

Somnopolygraphic recordings were registered from 29 patients with AIDS, their age ranged from 20 to 55 years (mean: 40.9; median: 44). The patients represent the full range of cerebral disintegration representing the picture of a progressing destruction of physiological sleep organization. Some disturbances begin quite early and progress successively, such as the reduction of REM- and delta-sleep as well as the reduction of sleep spindle- and K-complex-densities. Other changes are not manifest until intellectual capabilities break down; they occur massively such as the shortening of real sleep time and the reduction of sleep stage 2 with a simultaneous increase in waking time. It is remarkable that despite the enormous REM reduction there is no suppression of REM periods corresponding to "REM sine REM". REM periods become very short at an early stage; this is not only because the patients awake more frequently and earlier from their dream periods.

Somnopolygraphic recordings were registered from 29 patients with AIDS, their age ranged from 20 to 55 years (mean: 40,9; median: 44). The patients represent the full range of cerebral disintegration representing the picture of a progressing destruction of physiological sleep organization.

The amount of sleep spindles and K-complexes shows a great interindividual variety of combinations, such as many or few sleep spindles and K-complexes respectively. There seems to be no direct correlation between the amount of sleep spindles and K-complexes intraindividually. In our unselected population - age range between 18 and 77 years - the mean sleep spindle density is at 2.59 +/- 1.85/min and the mean K-complex density at 1.96 +/- .96/min stage 2. The diffuse individual distribution, however, does not reflect the age factor involved. The sleep spindle and K-complex density were practically half the amount for the age group above 50 years as compared to the age group of less than 30 years.

The high resolution capacity of nuclear magnetic resonance (NMR) imaging provides a sensitive tool for the detection of demyelinating plaques in the brainstem (Baum et al. 1986, Runge et al. 1984). The comparison of NMR and brainstem auditory evoked potentials (BAEPs) is aimed at clarifying the topographical informativeness of BAEPs (Kjaer 1980).