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PubMed2000

Nonlinear Markov process amplitude EEG model for nonlinear coupling interaction of spontaneous EEG.

To develop an appropriate model for representing spontaneous electroencephalography (EEG) is an important and necessary work in the field of neuroscience. The Markov process amplitude (MPA) EEG model has been proposed in our previous work for representing the features of the EEG in terms of a few parameters. However, being a linear model, the linear MPA EEG model cannot perfectly describe the spontaneous EEG that displays nonlinear phenomena. In this paper, the nonlinear Markov process amplitude (nonlinear MPA) EEG model that includes nonlinear components is introduced. The consistent consideration of the nonlinear features of the EEG investigated by N. Wiener and P. L. Nunez can be seen from the nonlinear MPA EEG model. The similarity in the time domain and the goodness of fitting in the frequency domain with respect to the ongoing EEG are shown. As a result, the EEG power spectrum can be decomposed into the spontaneous components and the nonlinearly coupled components by use of the nonlinear MPA EEG model, which is useful for a better understanding the mechanism of the EEG generation.

Biomedical Engineering↗

PubMed1995

[Analytic study on EEG features of aging with/without psychiatric disorders: focussing at the alterations in the EEGs of the healthy, depressive and demented elderlies].

The EEG alterations attributed to senescence are the complex result of functional as well as organic factors, such as normal physiological aging, pathological process which results in cognitive deterioration, and/or psychological phenomena including depression. The aim of this study is to clarify which factors influence which EEG features and to evaluate the relationship between the clinical and electrophysiological indices. For simplicity, this study focused on the major three factors that are important in dealing with senescence; 1) normal, physiological aging; 2) dementia; 3) depression. A total of 191 subjects participated in this study. The subject groups were classified into 9 groups based on their age and pathology. Two healthy elderly groups (N = 60; between the ages of 60 and 80 years; subclassified according to their social activity), a healthy young volunteers' group (N = 30; between the ages of 20 and 39), a healthy middle-aged volunteers' group (N = 30; between the ages of 40 and 59), four subject groups of dementia of Alzheimer's type [DAT] classified according to the severity of dementia (total number of subjects = 44), depressive elderly subjects (N = 12), and one group of subjects who are older than 80 years (N = 15). The depressive subjects were diagnosed as major depression with their main symptom being psychomotor retardation which resembles the clinical picture of early dementia. The EEGs change with age. This well-approved fact is also confirmed in this study based on ANOVA. Within the same age groups, there were little differences in EEGs regardless of the quality of their social activities. More slow activity, more 20-32Hz fast activity, and less 13.5-20.0Hz beta activity were seen in the socially-inactive group than in the socially-active group (multiple range test based on Tukey's method). The fact that no tendency of increases in slow and fast activities accompanied by a decrease of alpha activity were seen in the socially-active group suggest that having such tendency in their EEG features may be indicative of underlying pathological process that are qualitatively different from normal physiological aging. The moderate grade of those change may not yet cause clinical impairment noticeable as dementia, but appear as less social activity. The EEGs of depressed elderly differed from the socially-inactive elderly as well as the mild dementia particularly in beta frequency bands. There were no significant differences between the socially-inactive elderly and the mild dementia. The tendency of an increase of slow activity and a decrease of alpha activity was seen as the clinical severity of dementia increases. However, these changes reached at the statistically significant level only in the extremely demented subject group. To extract the feature indices of the EEGs, PCA was applied. Five principal components were descriptive of 88% of the data. The EEG features summarized by these components could differentiate the socially-active elderly and the socially-inactive elderly, and the depressed group was distinctively differed from other groups. Interestingly PCA showed the similarity between the socially-inactive elderly and the mild dementia, and the similarity between the middle-aged and the young volunteers. Except for the extreme dementia, subgroups of DAT patients according to the clinical severity did not show distinctive differences in EEG features. The correlation among the EEG derivations was investigated using cluster analysis. The result indicated that the interhemispheric electrophysiological correlation diminishes along with the advancement of the pathological process of the brain. This study indicated that the EEG indices derived from the multivariate analyses are more informative in regard to the relationship among EEG variables as well as these spatial relationship than evaluating the changes in each frequency band alone.

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↗

PubMed1981

A comparative study of the diagnosis value of drug-induced sleep EEGs and sleep EEGs following sleep deprivation in patients with complex partial seizures.

The purpose of the study was to investigate whether the sleep EEG after sleep deprivation has a stronger provocative effect than the drug-induced sleep EEG. For this purpose a sleep EEG, induced by 2 mg/kg body weight of promazine hydrochloride, was recorded. On the following day a sleep EEG of the same patient was recorded after sleep deprivation of 24--26 h. If only patients whose wake EEGs were free from epileptic activity are considered, the rate of provocation was 58%. As epileptic activity could be recorded even in the sleep EEG without sleep deprivation in 45%, the advantage gained by recording a sleep EEG after sleep deprivation (52%) is only relatively small. The occurrence of epileptic activity was shown to be significantly more frequent amongst women and those who developed epilepsy at a younger age. For practical purposes it is recommended that for those patients whose wake EEGs are free from epileptic activity, a sleep EEG--possibly drug-induced--should be recorded. Only in instances where epileptic activity can not then be recorded should a wake EEG after sleep deprivation be carried out, and followed immediately, if necessary, by a sleep EEG.

Adolescent↗

PubMed1980

Quantitative analysis of training, sleep EEG and clinical response to EEG operant conditioning in epileptics.

This report is a follow-up to a previous paper which described seizure rate changes with central cortical EEG feedback training in 8 poorly controlled epileptic subjects. Data examined here include associated training compliance and performance, sleep EEG spectra, clinical EEG and anticonvulsant blood levels. The study employed a double-cross-over, single blind ABA design applied to two subgroups of epileptic patients. Both groups had in common two training periods (A1, A2) in which either 12--15 c/sec (subgroup I, n = 4) or 18--23 c/sec (subgroup II, n = 4) was reinforced in the absence of 6--9 c/sec, movement or epileptiform discharge, and one training period (B) in which 6--9 c/sec was reinforced in the absence of 12--15 or 18--23 c/sec as well as movement and epileptiform discharge. Training periods occurred primarily in the home and lasted 3 months. Compliance with training instructions and response acquisition were demonstrated. Overall anticonvulsant blood levels were low and unrelated to EEG or seizure changes. Clinical EEG findings corresponded to sleep EEG and seizure rate outcomes. Power spectral analysis of sampled non-REM sleep from all-night EEG recordings obtained after each training phase indicated contingency specific changes which were limited to sensorimotor recordings in subgroup I and corresponded to the pattern of seizure rate changes in this group. EEG changes were also limited to sensorimotor cortex in subgroup II, but were linear and paralleled a progressive decrease in seizure rate. Both groups, however, showed the same pattern of EEG changes with seizure reductions; low and high frequencies were reduced and intermediate, rhythmic frequencies increased. Correlational analysis confirmed this relationship. The pattern, duration and topographic specificity of these changes suggested a normalization of sensorimotor EEG substrates related to the EEG feedback traning.

Adolescent↗

PubMedDate not supplied

Mu-delta opioid interactions. III: Differential antagonism of DPDPE-induced increases in morphine EEG and EEG power spectra by DALCE and naltrindole.

In the present study, the effects of DALCE ([D-Ala2,Leu5,Cys6]enkephalin) and naltrindole on DPDPE ([D-Pen2,D-Pen5]enkephalin)-induced increases in morphine EEG and EEG power spectra were assessed. Adult female Sprague-Dawley rats were implanted with cortical EEG electrodes and permanent indwelling ICV and IV cannulae. Rats were pretreated with ICV DALCE at 15.7 nmol, ICV naltrindole at 20 nmol, or ICV sterile water. Rats were then administered ICV DPDPE at 2.5 nmol or ICV sterile water followed, 10 min later, by IV morphine at 3 mg/kg. Morphine-induced changes in EEG global (1-50 Hz) spectral parameters, the duration of morphine-induced high-voltage EEG bursts, the duration of EEG and behavioral excitation, and the latency to onset of slow-wave sleep were assessed. The DALCE pretreatment significantly decreased morphine-induced total spectral power seen in the DPDPE + morphine group. The DALCE pretreatment reversed the effects of DPDPE on the duration of morphine-induced EEG bursts and the duration of EEG and behavioral excitation. The ICV naltrindole, however, had no significant effect on DPDPE-induced increases in morphine EEG, EEG spectral parameters, and behavior. These data, therefore, suggest that DPDPE may be increasing the effects of morphine on EEG through DALCE-sensitive delta opioid receptors associated within the mu-delta opioid receptor complex.

Analgesics↗

PubMed2006

Interictal EEG as a physiological adaptation. Part II. Topographic variability of composition of brain oscillations in interictal EEG.

OBJECTIVE: In the present experimental study, we examined topographic variability of composition of brain oscillations and their temporal behavior in frequencies from 0.5 to 30 Hz of interictal EEG without epileptiform abnormalities and healthy EEG. METHODS: Spatio-temporal variability of brain oscillations (indexed by short-term EEG spectral patterns (SPs)) was assessed by the probability-classification analysis of SPs. As a result, multi-dimensional SP-vector for each analysis EEG epoch was obtained. RESULTS: It was demonstrated that interictal EEG was characterized (a) by a significant decrease of spatio-temporal variability of brain oscillations, (b) by longer periods of temporal stabilization for operational modules which comprise larger number of cortical areas, and (c) by significantly more intermittent recurrence when compared with EEG of control subjects. Generally it was shown that EEG channels display different states of coordination independently on their correlation and coherence using brain oscillations at multiple frequencies. CONCLUSIONS: Results of this study suggested that EEG correlate of chronic epileptogenesis in the brain is a particular metastable state of biopotential field, which can be estimated by SP-vector. The fact that all results were significantly different from surrogate EEGs reflects a nonoccasional and thus, most likely, an adaptive nature of spatio-temporal reorganization in interictal EEG. SIGNIFICANCE: Parameters of spatio-temporal organization of interictal EEG without the signs of epileptiform activity can be considered as additional information in premorbid diagnostics of status epilepticus, and may also provide insights into basic laws that govern brain oscillations in general.

Action Potentials↗

PubMed2006

Source analysis of EEG oscillations using high-resolution EEG and MEG.

We investigated spatial properties of the source distributions that generate scalp electroencephalographic (EEG) oscillations. The inherent complexity of the spatio-temporal dynamics of EEG oscillations indicates that conceptual models that view source activity as consisting only of a few "equivalent dipoles" are inadequate. We present an approach that uses volume conduction models to characterize the distinct spatial filtering of cortical source activity by average reference EEG, high-resolution EEG, and magnetoencephalography (MEG). By comparing these three measures, we can make inferences about the sources of EEG oscillations without having to make prior assumptions about the sources. We apply this approach to spontaneous EEG oscillations observed with eyes closed at rest. Both EEG and MEG recordings show robust alpha rhythms over posterior regions of the cortex; however, the dominant frequency of these rhythms varies between EEG and MEG recordings. Frontal alpha and theta rhythms are generated almost exclusively by superficial radial dipole layers that generate robust EEG signals but very little MEG signals; these sources are presumably mainly in the gyral crowns of frontal cortex. MEG and high-resolution EEG estimates of alpha rhythms provide evidence of local tangential and radial sources in the posterior cortex, lying mainly on sulcal and gyral surfaces. Despite the detailed information about local radial and tangential sources potentially afforded by high-resolution EEG and MEG, it is also evident that the alpha and theta rhythms receive contributions from non-local source activity, for instance large dipole layers distributed over lobeal or (potentially) even larger spatial scales.

Animals↗

PubMed1992

Comparison of EEG between nasopharyngeal and scalp leads with the aid of an automatic EEG analysis system.

We analyzed the EEG quantitatively with an automatic EEG analysis system, and introduced this system for investigation the relationship between the scalp EEG and nasopharyngeal EEG. The EEG was recorded from healthy volunteers by photic stimulation. We found that components of slow waves like delta and theta were more rich but alpha component was less in the nasopharyngeal EEG than in the scalp EEG. In the analysis of the rate of the appearance of each EEG wave using photic stimulus, a decrease of alpha 1 and an increase of theta 1 are observed in the scalp EEG while there are no specific changes of them in the nasopharyngeal and scalp EEGs. The nasopharyngeal EEG obtained from the vicinity of the base of the brain was thought to originate from the vicinity of the brain stem.

Adult↗

PubMed1993

[Topographic-quantitative EEG-analysis of the paradoxical arousal reaction. EEG changes during urologic surgery using isoflurane/ N2O anesthesia].

Increases in slow-wave (delta) activity in the EEG may reflect increased depth of anaesthesia provided that hypoxia, haemodynamic instability and drug overdose have been excluded. In contrast, similar intraoperative EEG responses have been described as paradoxical arousal reactions. The aim of this study was to assess the effects of surgical stimulation on spatial EEG changes during anaesthesia with 0.6% isoflurane/66% nitrous oxide. METHODS. The present study investigated changes in EEG power and frequencies in 20 patients (mean age 36 +/- 8 years; ASA I or II) scheduled for elective urological surgery during steady-state anaesthesia with 0.6% isoflurane and 66% nitrous oxide. The following variables were measured: heart rate (HR), mean arterial blood pressure (MAP), end-tidal isoflurane (PetISO) and carbon dioxide concentrations (PetCO2), arterial oxygen saturation (SaO2%) and body temperature (degree C). Patients were randomly assigned to one of two groups: group 1 (n = 10; without surgery) and group 2 (n = 10; with surgical procedure). The EEG was recorded over 20 min. The first 5 min were taken as baseline. In group 2 surgical stimulation (skin incision with subsequent surgical preparation) was started 1-2 min after recording of baseline values. Topographical distribution of EEG output was recorded from 17 electrodes (international 10-20 system), digitized and stored on disk (CATEEM) after establishment of steady-state anaesthesia (PetISO: 0.6%; PetCO2: 35-37 mmHg). Data are given as medium (microV2/Hz) and relative changes (%) +/- SD with respect to baseline. Statistical significance was tested for F4 versus C4 for the delta- and alpha-1-frequency bands using Wilcoxon's test (P < 0.05). RESULTS. In group 1 (without surgical stimulation) all parameters did not change over time. EEG slowing with an increase in power (> 100%) was noted in 8 patients of group 2 (n = 10; during surgical stimulation). By visual inspection of the original EEG tracings paradoxical arousal patterns were seen in these patients. In group 2, delta output changed from 69.6 microV2/Hz (baseline) to 147.4 microV2/Hz at frontal leads (F4) 5-6 min after the start of surgery. Only minimal changes were observed for theta activity. At the same time, in most cases fast wave activity (alpha 1, alpha 2, beta 1 and beta 2) was decreased by more than 50% at identical cortical areas. Increases in MAP were noted continuously after start of surgery up to a maximum of 19.8% from baseline, which became significant at the 16-min level. Heart rate did not change over time. DISCUSSION. Our data demonstrate that EEG slowing may be induced by surgical stimulation during steady-state anaesthesia with 0.6% isoflurane/66% nitrous oxide in oxygen. These findings are consistent with previous reports indicating the occurrence of slow wave patterns following sensory stimulation in comatose patients. Since these events occur predominantly at frontal areas they may not be detected with single-channel parietal recordings. Our data suggest that topographical EEG monitoring may useful for assessing painful events during surgery. Using EEG monoparameters like spectral edge frequency or median the occurrence of paradoxical arousal reactions may be falsely interpreted as an increased depth of anaesthesia.

Adult↗

PubMed1992

Naltrindole retards tolerance development to morphine-induced effects on EEG and EEG power spectra.

In the present study, EEG and EEG power spectra were used to assess the effects of naltrindole, a selective delta opioid antagonist, on the development of tolerance to morphine. Adult female Sprague-Dawley rats were implanted with cortical EEG electrodes and permanent indwelling i.c.v. and i.v. cannulas. Twice daily for 7 days, rats were pretreated with either i.c.v. naltrindole (20 nmol) or i.c.v. water, 20 min before i.v. morphine (10 mg/kg) injections. The treatments produced EEG slow-wave bursts and associated behavioral stupor. The amount and duration of these effects decreased less rapidly over the 7 days in the naltrindole-pretreated rats than in the water-pretreated rats. I.c.v. naltrindole pretreatment also prevented significant decreases in latency to onset of slow-wave sleep that were seen in the i.c.v. water-pretreated group. EEG data were further analyzed on a Pathfinder II computer. The development of tolerance was reflected by decreases in the total absolute EEG spectral power (1-50 Hz) over the 7-day period. Rats that were pretreated with i.c.v. naltrindole (20 nmol) did not display a significant decrease in total absolute EEG spectral power by the 7th day, as did the i.c.v. water-pretreated group. Furthermore, significant differences were seen for complexity, mobility, and edge frequency between the two pretreatment groups. A delayed qualitative change in the EEG power spectra was also observed in rats pretreated with i.c.v. naltrindole. On day 1, EEG slow-wave bursts were associated with increases in EEG spectral power over the 1-10 Hz range.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

PubMed2005

Correspondence between EEG-fMRI and EEG dipole localisation of interictal discharges in focal epilepsy.

EEG-fMRI and EEG dipole source localisation are two non-invasive imaging methods that can be applied to the study of the haemodynamic and electrical consequences of epileptic discharges. Using them in combination has the potential to allow imaging with the spatial resolution of fMRI and the temporal resolution of EEG. However, although considerable data are available concerning their concordance in studies involving event-related potentials (ERPs), less is known about how well they agree in epilepsy. To this end, 17 patients were selected from a database of 57 who had undergone an EEG-fMRI scanning session followed by a separate EEG session outside of the scanner. Spatiotemporal dipole modelling was compared with the peak and closest EEG-fMRI activations and deactivations. On average, the dipoles were 58.5 mm from the voxel with the highest positive t value and 32.5 mm from the nearest activated voxel. For deactivations, the corresponding values were 60.8 and 34.0 mm. These values are considerably higher than is generally observed with ERPs, probably as a result of the relatively widespread field, which can lead to artificially deep dipoles, and the occurrence of EEG-fMRI responses remote from the presumed focus of the epileptic activity. The results suggest that EEG and MEG inverse solutions for equivalent current dipole approaches should not be strongly constrained by EEG-fMRI results in epilepsy, and that the use of distributed source modelling will be a more appropriate way of combining EEG-fMRI results with source localisation techniques.

Data Interpretation, Statistical↗

PubMed1996

Muscle artifacts in the sleep EEG: automated detection and effect on all-night EEG power spectra.

Owing to the use of scalp electrodes in human sleep recordings, cortical EEG signals are inevitably intermingled with the electrical activity of the muscle tissue on the skull. Muscle artifacts are characterized by surges in high frequency activity and are readily identified because of their outlying high values relative to the local background activity. To detect bursts of myogenic activity a simple algorithm is introduced that compares high frequency activity (26.25-32.0 Hz) in each 4-s epoch with the activity level in a local 3-min window. A 4-s value was considered artifactual if it exceeded the local background activity by a certain factor. Sensitivity and specificity of the artifact detection algorithm were empirically adjusted by applying different factors as artifact thresholds. In an analysis of sleep EEG signals recorded from 25 healthy young adults 2.3% (SEM: 0.16) of all 4-s epochs during sleep were identified as artifacts when a threshold factor of four was applied. Contamination of the EEG by muscle activity was more frequent towards the end of non-REM sleep episodes when EEG slow wave activity declined. Within and across REM sleep episodes muscle artifacts were evenly distributed. When the EEG signal was cleared of muscle artifacts, the all-night EEG power spectrum showed significant reductions in power density for all frequencies from 0.25-32.0 Hz. Between 15 and 32 Hz, muscle artifacts made up a substantial part (20-70%) of all-night EEG power density. It is concluded that elimination of short-lasting muscle artifacts reduces the confound between cortical and myogenic activity and is important in interpreting quantitative EEG data. Quantitative approaches in defining and detecting transient events in the EEG signal may help to determine which EEG phenomena constitute clinically significant arousals.

Adolescent↗

PubMed2000

Interictal EEG and ictal scalp EEG propagation are highly predictive of surgical outcome in mesial temporal lobe epilepsy.

PURPOSE: Surgical outcome in patients with mesial temporal lobe sclerosis (MTS) is worse than that in patients with temporal lobe activity (TLE) with tumors. Previous studies of the ictal EEG focused on ictal EEG onset in scalp EEG or ictal EEG propagation in invasive recordings. Ictal EEG propagation with scalp electrodes has not been reported. METHODS: Ictal scalp EEG propagation patterns were studied in 347 seizures of 58 patients with MTS or nonlesional TLE. Interictal epileptiform discharges (IEDs) and the presence of unilateral mesial temporal lobe atrophy in magnetic resonance imaging (MRI) also were studied in these 58 patients. Forty-nine patients were operated on (minimal follow-up of 1 year). RESULTS: Postoperatively, seizure-free outcome was seen in (a) 82.8% of patients with regionalized EEG seizure without contralateral propagation, but in only 45.5% of patients with contralateral propagation (p = 0.007); (b) 84.6% of patients with 100% IED lateralized to one temporal lobe, but in only 52.2% with <100% unitemporal IED (p = 0.015); (c) 88.9% with 100% unitemporal IED and regionalized ictal EEG combined, 73.7% with one of both variables, and only 33.3% with <100% ipsitemporal IED combined with contralateral ictal EEG propagation (p = 0.007). CONCLUSIONS: Switch of lateralization or bitemporal asynchrony in the ictal scalp EEG and bitemporal IED are most probably an index of bitemporal epileptogenicity in MTS and are associated with a worse outcome.

Adolescent↗

PubMed1987

[Value of quantitative EEG and EEG mapping in medicine].

Quantitative EEG consists in digitising the EEG from one or several leads and then mathematically processing the signal usually by Fourier spectral analysis. A reduction of the digital information gives characteristic parameters (frequency, amplitude or power, asymmetry, etc.), which can themselves be averaged and submitted to different statistical analysis. Quantitative EEG is particularly suitable for clinical electropharmacology for the assessment of the profiles of psychotropic drugs, for pharmacokinetic correlations of dose-effect relationships and studies of drug bioavailability. The signals obtained from schizophrenic and depressed patients have well defined quantitative EEG characteristics: dissymmetry of the amplitude and hypovariability of the EEG signals. EEg mapping is performed by computer processing of 16 simultaneous EEG lead recordings. This new form of medical imaging is fast, relatively economical and non-invasive, and it is used in psychophysiology to study cognitive tasks and the states of vigilance and sleep. It is also used to study the EEG topography of cerebrovascular accidents, brain tumours, cranial trauma, cerebral degeneration and dementia, and the EEGs of psychiatric patients on psychotropic drugs. EEG mapping represents not only a static and statistical approach by drawing the averaged maps of groups of patients but also a dynamic approach by the recording of sequential individual maps presented as an animated film. The results of this method can be correlated with other medical imaging techniques used to investigate the central nervous system.

Brain Diseases↗

PubMed1986

Electroencephalographic (EEG), EEG power spectra, and behavioral correlates in rats given phencyclidine.

The electroencephalogram (EEG), electromyogram (EMG) and behavior were monitored in rats with chronic cerebrocortical and temporalis muscle electrodes. They were injected acutely with 0, 2, 4 and 8 mg/kg of phencyclidine (i.p.). The EEG power spectra correlated in a dose-related manner, with the direct EEG and behavioral effects of phencyclidine. At 2 mg/kg, the EEG consisted primarily of low amplitude theta activity from 6 to 8 Hz, accompanied by behavioral arousal and hyperactivity. At 4 mg/kg, the EEG theta activity persisted and was superimposed on a background of high amplitude slow waves which were associated with the emergence of ataxia. Locomotion and stereotypy intensified at this dose. The power spectra of these changes in the EEG were characterized by two distinct spectral peaks lying between 0-5 and 5-10 Hz. After 8 mg/kg, EEG activity shifted predominantly to lower frequencies between 2 and 3 Hz. This shift produced a large increase in spectral power in the 0-5 Hz band which was accompanied behaviorally by severe ataxia, limited locomotion, and stereotypy of head and forepaw movements. Similarities and differences between these EEG changes induced by phencyclidine and the EEG effects of ketamine and SKF 10047 were obtained.

Animals↗

PubMedDate not supplied

Mu-delta opioid interactions. II: Beta-FNA inhibits DPDPE-induced increases in morphine EEG and EEG spectral power.

In the present study, the effects of beta-FNA on DPDPE-induced increases in morphine EEG and EEG power spectra were assessed. Adult female Sprague-Dawley rats were implanted with cortical EEG electrodes and permanent indwelling ICV and IV cannulae. Rats were administered ICV beta-FNA at 20 nmol or ICV sterile water. Then 18-24 h later, rats were administered ICV DPDPE at 2.5 nmol or ICV sterile water followed, 10 min later, by IV morphine at 3 mg/kg. Morphine-induced changes in EEG global (1-50 Hz) spectral parameters, the duration of morphine-induced high voltage EEG bursts, the period of EEG and behavioral excitation, and the latency to onset of slow-wave sleep were statistically analyzed using a one-way analysis of variance. beta-FNA pretreatment significantly decreased morphine-induced total spectral power seen in the DPDPE + morphine group. beta-FNA pretreatment also significantly decreased the duration of morphine-induced EEG bursts, the period of EEG and behavioral excitation, and the latency to onset of slow-wave sleep in the DPDPE + morphine group. These data, therefore, suggest that DPDPE may be increasing the effects of morphine on EEG through delta opioid receptors associated with the mu-delta opioid receptor complex.

Analgesics↗

PubMed2003

Computerized processing of EEG-EOG-EMG artifacts for multi-centric studies in EEG oscillations and event-related potentials.

The aim of this study is to present a package including standard software for the electroencephalographic (EEG), electro-oculographic (EOG) and electromyographic (EMG) preliminary data analysis, which may be suitable to standardize the results of many EEG research centers studies (i.e. multi-centric studies) especially focused on event-related potentials. In particular, our software package includes (semi)automatic procedures for (i) EOG artifact detection and correction, (ii) EMG analysis, (iii) EEG artifact analysis, (iv) optimization of the ratio between artifact-free EEG channels and trials to be rejected. The performances of the software package on EOG-EEG-EMG data related to cognitive-motor tasks were evaluated with respect to the preliminary data analysis performed by two expert electroencephalographists (gold standard). Due to its extreme importance for multi-centric EEG studies, we compared the performances of two representative "regression" methods for the EOG correction in time and frequency domains. The aim was the selection of the most suitable method in the perspective of a multi-centric EEG study. The results showed an acceptable agreement of approximately 95% between the human and software behaviors, for the detection of vertical and horizontal EOG artifacts, the measurement of hand EMG responses for a cognitive-motor paradigm, the detection of involuntary mirror movements, and the detection of EEG artifacts. Furthermore, our results indicated a particular reliability of a 'regression' EOG correction method operating in time domain (i.e. ordinary least squares). These results suggest that such a software package could be used for multi-centric EEG studies.

Algorithms↗