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At least 109 records · Page 6Linked to original sources
PubMed2001

EEG evidence for shunt requirement during carotid endarterectomy: optimal EEG derivations with respect to frequency bands and anesthetic regimen.

Currently there is no consensus on the derivations that should be used for EEG monitoring during carotid endarterectomy (CEA). The aim of this study was to determine which derivations distinguish the best between patients requiring a shunt and patients who do not need a shunt. Four predefined frequency bands and two regimens for general anesthesia (isoflurane versus propofol) were used. EEG data (16 channels) were obtained from 152 EEGs recorded during carotid endarterectomy. Analog EEG signals of preclamp and clamp periods of 100 seconds were digitized to compute power spectra. Changes in power during clamping were calculated for all possible derivations in four predefined frequency bands and were expressed as Z-scores. For each derivation, the area under the receiver operating characteristics curve was calculated. Derivations with the greatest area under the receiver operating characteristics curve were considered to distinguish the best between the shunt and the nonshunt groups formed in retrospect on the basis of consensus between three independent and experienced board-certified electroencephalographers. The two different anesthetic regimens resulted in different patterns of EEG changes because of clamping. The optimal derivations to differentiate between the shunt and the nonshunt groups also differed for the two anesthetic regimens, although for both conditions, anterior head regions were especially preferred. The optimal derivations are given for each anesthetic regimen.

Adult↗
PubMed2003

EEG changes accompanying learned regulation of 12-Hz EEG activity.

We analyzed 15 sessions of 64-channel electroencephalographic (EEG) data recorded from a highly trained subject during sessions in which he attempted to regulate power at 12 Hz over his left- and right-central scalp to control the altitude of a cursor moving toward target boxes placed at the top-, middle-, or bottom-right of a computer screen. We used infomax independent component analysis (ICA) to decompose 64-channel EEG data from trials in which the subject successfully up- or down-regulated the measured EEG signals. Applying time-frequency analysis to the time courses of activity of several of the resulting 64 independent EEG components revealed that successful regulation of the measured activity was accompanied by extensive, asymmetrical changes in power and coherence, at both nearby and distant frequencies, in several parts of cortex. A more complete understanding of these phenomena could help to explain the nature and locus of learned regulation of EEG rhythms and might also suggest ways to further optimize the performance of brain-computer interfaces.

Adaptation, Physiological↗
PubMed1997

Occurrences of electroencephalographic (EEG) patterns that resemble epileptiform discharges in background EEG in epileptic patients.

The relationships of background EEG to epileptiform discharge development were studied in 9 epileptic patients having generalized spike and wave complexes (SWCs) with a maximum at the frontal location on either side. The instantaneous power spectrum of EEGs at F3, F4, C3, C4, P3, P4, O1, O2, T3 and T4 was estimated with wavelet transform. Subsequently, the similarity of power spectra between SWCs and background EEG was determined by use of Kullback-Leibler information and artificial neural network in each patient. Both similarity measures revealed that EEG patterns similar to SWCs occurred in the background activity just before SWCs at frontal locations. These findings suggested that these SWC-like EEG events occurred as poorly developed epileptiform discharges buried in the background activity.

Adolescent↗
PubMed2001

[Study of EEG processing system and EEG wavelet transform].

In this paper are reported our studies on the time and frequency characteristics of wavelet transform, the EEG signals processing through wavelet transform, the EEG analysis and reconstruction results. The related EEG processing system design and implementation are given in detail. This system may be applied to EEG feedback research and EEG monitoring.

Computers↗
PubMed2001

Neonatal seizures: background EEG activity and the electroclinical correlation in full-term neonates with hypoxic-ischemic encephalopathy. Analysis by computer-synchronized long-term polygraphic video-EEG monitoring.

Between 1994 and 2000, 30 full-term newborns affected by seizures secondary to hypoxic-ischemic encephalopathy, underwent computerised, polygraphic, video-EEG recordings during the first 48 hours of life, in our neonatal intensive care unit. In this longitudinal study, recordings lasted an average of 10.5 hours. We studied EEG ictal discharges that lacked a clinical correlate, the semeiotics, and the electroclinical correlation during seizures, by reviewing the time-synchronised, video-EEG recordings obtained during these six years. The aim of this investigation was to evaluate the relationship between background EEG activity and the electroclinical correlation or dissociation of the seizures. When background activity was depressed and undifferentiated, the seizures were characterised by the electroclinical dissociation except in instances of focal tonic seizures. With all other background patterns, seizures were invariably accompanied by the electrical correlate, the only exception being ocular signs and oral-buccal-lingual movements, which occurred both with and without paroxysmal discharges. Ocular signs and oral-buccal-lingual movements were very frequent and were observed with all patterns of background activity. Only on one occasion were they the sole clinical expression of seizures. In our patients, the electroclinical dissociation was constant only if background EEG activity was depressed and undifferentiated. The constant electroclinical dissociation of seizures was closely correlated with the type of background activity, which, in turn, is indicative of severe cerebral damage. (Published with videosequences.)

Cerebral Cortex↗
PubMed2002

Classification and evaluation of the pharmacodynamics of psychotropic drugs by single-lead pharmaco-EEG, EEG mapping and tomography (LORETA).

Utilizing computer-assisted quantitative analyses of human scalp-recorded electroencephalogram (EEG) in combination with certain statistical procedures (quantitative pharmaco-EEG) and mapping techniques (pharmaco-EEG mapping), it is possible to classify psychotropic substances and objectively evaluate their bioavailability at the target organ: the human brain. Specifically, one may determine at an early stage of drug development whether a drug is effective on the central nervous system (CNS) compared with placebo, what its clinical efficacy will be like, at which dosage it acts, when it acts and the equipotent dosages of different galenic formulations. Pharmaco-EEG profiles and maps of neuroleptics, antidepressants, tranquilizers, hypnotics, psychostimulants and nootropics/cognition-enhancing drugs will be described in this paper. Methodological problems, as well as the relationships between acute and chronic drug effects, alterations in normal subjects and patients, CNS effects, therapeutic efficacy and pharmacokinetic and pharmacodynamic data will be discussed. In recent times, imaging of drug effects on the regional brain electrical activity of healthy subjects by means of EEG tomography such as low-resolution electromagnetic tomography (LORETA) has been used for identifying brain areas predominantly involved in psychopharmacological action. This will be demonstrated for the representative drugs of the four main psychopharmacological classes, such as 3 mg haloperidol for neuroleptics, 20 mg citalopram for antidepressants, 2 mg lorazepam for tranquilizers and 20 mg methylphenidate for psychostimulants. LORETA demonstrates that these psychopharmacological classes affect brain structures differently.

Brain Mapping↗
PubMed1991

Short-term sleep EEG recordings after partial sleep deprivation as a routine procedure in order to uncover epileptic phenomena: an evaluation of 719 EEG recordings.

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.

Adolescent↗
PubMed1981

Analysis of the time series of the EEG frequency spectra and of EEG spectral power densities.

Some examples of the use of the principal component model for the economic description of the structure of the multiple time series and for the data reduction in the quantitative EEG studies are presented. The broad-band EEG frequency spectra were measured with the use of an electronic system designed by J. Dvorák. The EEG spectral power densities were computed via the discrete Fourier Transform (namely FFT) algorithm. The estimated two or three first principal components account for the major part of the total variance of individual EEG variables: The results hold for the used elementary epoch of measurement, i.e. 5 sec. - With the use of the algorithms and FORTRAN IV programs developed by J. Andĕl, T. Cipra and L. Tomásek a data reduction by a factor of 1:2000 can be achieved without any substantial loss of biological information. - The described methods help to obtain a better insight into the structure of the data and represent a powerful tool for data reduction at least in a certain class of experimental EEG studies (experimental toxicology, pharmacology, experimental neurology).

Animals↗
PubMed1990

EEG cartography before and after visual stimulation: a group study with descriptive non-parametric analysis of EEG data.

Ten right-handed students were submitted to a protocol of cognitive visual stimulations based on six successive sequences: EC1, EO, B1, B2, B3, EC2. Following a first "eyes closed" (EC1) multiple EEG recording (16 EEG leads, plus polygraphy), and an "eyes-open" recording (EO) with central visual fixation, 60 computer-controlled slides were presented successively for each of three successive recordings (B1, B2, B3) before the last "eyes-closed" recording (EC2). In B1, the subjects were asked to look at the meaningful black and white drawings presented without comment. In B2, a second set of similar pictures was presented, with the advice to try to remember later on the visually projected slides. In B3, a memory recognition task was introduced with 20 slides coming from the B1 set, 20 from the B2 set, completed by 20 new slides. Each slide was presented for 10.24s. followed by a beep audio-signal indicating that the subjects should press electronic mouse knobs alternatively in B1, B2, and for indicating their answers in B3. After artifact rejection, EEG spectral analysis was followed by parametrization and group studies applying Fisher non-parametric paired exact probability tests. Nine comparisons were computed: EC1-EC2, EC1-EO, EC2-EO, EO-B1, EO-B2, EO-B3, B1-B2, B1-B3, B2-B3. A statistical strategy of descriptive inter-individual non-parametric. Fisher tests was undertaken, together with computation and mapping of averaged spectral parameter differences (mean amplitudes and frequencies, mean amplitudes %, resonance coefficients) for raw EEG, delta, theta, alpha, alpha 1, alpha 2, beta 1 and beta 2 frequency bands and probability maps.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗
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↗
PubMed1989

Correction of ocular artifacts in EEGs using an autoregressive model to describe the EEG; a pilot study.

The basic idea in eye movement (EM) artifact corrections is that the actual recording is the summation of brain potentials (true EEG) and artifact. Often a regression analysis is performed, using simultaneous EEG and EOG data, to find the parameters describing the relationship between artifact and EOG derivations (EOGs). Our method uses a maximum likelihood parameter estimation and considers data from preceding sample moments as well, since there may be a delay in the artifact transferring over the scalp. For the error term (true EEG) an autoregressive function is used. Results from estimations on data from one volunteer indicate that a delay need not be considered and that 3 autoregressive parameters are sufficient. For F3 4 EOGs give only somewhat better results than 2 EOGs. For C3 and C4 2 EOGs are sufficient. For practical reasons for each of these 3 EEG recordings, 2 EOGs were used to perform corrections. Corrections were performed using either the parameters estimated for EMs and blinks together, or the parameters estimated for EMs only (used for EMs), or the parameters estimated for blinks only (used for blinks). For EMs the differences between these corrections are very small. For blinks the differences are much larger. Parameters estimated for one trial may be used to correct other trials, recorded within a period of about 15 min preceding or following that trial.

Blinking↗
PubMed1994

EEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures.

Attempts to classify Alzheimer's disease (AD) subjects versus controls using spectral-band measures of electroencephalographic (EEG) data typically achieve around 80% success. This study assessed the ability of adding non-linear EEG measures and using a neural-net classification procedure to improve this performance level. The non-linear EEG measures were estimated correlation dimension ("dimensional complexity," or DCx) and saturation (degree of leveling-off of DCx with increasing embedding dimension). In a sample of 39 subjects (14 ADs, 25 controls), it was found that (a) the addition of non-linear EEG measures improved the classification accuracy of the AD/control status of subjects, and (b) a back-percolation neural net predictively classified the subjects much better than the standard linear techniques of multivariate discriminant analysis or nearest-neighbor discriminant analysis.

Aged↗
PubMed1993

Interactions between U-50,488H and sigma receptor antagonists: EEG, EEG power spectral and behavioral correlates.

I.v. administration of U-50,488H after i.v. saline pretreatment produced occasional high-voltage EEG slow-wave bursts that were associated with relatively small increases in spectral power in the 2.5-7.5 Hz band as a spectral peak and with behavioral incidents of sedation, ataxia, ptosis, straub tail, hunching of the back, and backing-up. After pretreatment with the sigma antagonists rimcazole and DuPont Merck S-7389-4, U-50,488H administration produced significantly larger increases in absolute EEG spectral power, both over the 1-50 Hz range and in the 2.5-5.0 and 5.0-7.5 Hz bands, than after saline pretreatment; rimcazole pretreatment eliminated U-50,488H-induced incidents of ataxia, ptosis, hunching of the back and backing-up. In summary, effects of U-50,488H on EEG, EEG power spectra and behavior may reflect interactions between kappa opioid and sigma (non-opioid) receptor-effector systems.

3,4-Dichloro-N-methyl-N-(2-(1-pyrrolidinyl)-cycloh↗
PubMed1994

Interactive effects of MK-801 and morphine on EEG, EEG power spectra and behavior in rats: II. Morphine dependence.

A potential interaction between MK-801 and the cortical electroencephalographic (EEG) and behavioral expressions of morphine dependence in female Sprague-Dawley rats was assessed. Rats were treated chronically (7 days) with either morphine alone, morphine and MK-801, MK-801 alone or saline vehicle alone. On day 8 all rats received morphine alone followed by naloxone. An additional group received chronic (7 days) morphine alone, followed by MK-801 on day 8 prior to morphine and naloxone. Naloxone-induced EEG complexity in morphine-dependent rats was significantly lower than in chronic saline-treated rats. Total power, mobility, mean frequency, complexity and edge frequency in response to naloxone-induced withdrawal in morphine-dependent rats were significantly altered from those in chronically MK-801 alone-treated rats. No differences were found in the EEG and behavioral responses to naloxone between rats that received chronic MK-801 and those that didn't during chronic morphine treatment. Acute MK-801 prior to naloxone in morphine-dependent rats attenuated the behavioral, but not the EEG response to naloxone-induced withdrawal.

Animals↗
PubMed1993

Ammonia-independent modifications of the background EEG signal and paradoxical enhancement of epileptic abnormalities in EEG after acute administration of valproate to epileptic patients.

The effects on the background quantitative EEG (power spectral analysis) and concentration of valproate in plasma were studied after single-dose (14.3-33.3 mg/kg) oral administration in 12 epileptic patients with generalized nonconvulsive or partial seizures. An increase of the amplitude of the background EEG (diffuse and preponderant on anterior scalp areas) and a decrease of the 12.5-32.0 Hz relative power (limited to the posterior electrode deviations) were observed; the increase in the EEG total power was paralleled by a definite increment in incidence of epileptic phenomena in the EEG. Both effects proved unrelated to shifts in vigilance or changes in the concentration of ammonia or serum glucose in plasma and confirm previous observations from superimposable study designs. These findings are qualitatively opposite to those observed during long-term treatment at comparable doses and are suggested to reflect a direct CNS action of acute administration of valproate.

Adolescent↗
PubMed2004

EEG dipole source localisation of interictal spikes acquired during routine clinical video-EEG monitoring.

OBJECTIVE: We investigated the feasibility of electroencephalography (EEG) dipole source localisation of interictal epileptiform discharges from data acquired during routine clinical inpatient video-EEG monitoring (VEM) and compared a 19-channel 'routine montage' with a 29-channel 'surgical montage' that includes an additional row of 10 inferior temporal electrodes. METHODS: Twenty consecutive patients who had VEM for the presurgical evaluation of medically refractory partial epilepsy were screened. Thirteen of the patients had focal interictal spikes recorded, and in 11 (85%) these were technically satisfactory for source localisation. Fourteen spike foci were analysed as 3 patients had bilateral independent spikes. EEG data was acquired with 29 electrodes including an inferior temporal row (surgical montage). For comparison, the 10 additional electrodes were excluded from analysis (routine montage). Using NEUROSCAN Source 2.0 software, a computed dipole source localisation of averaged spikes was performed utilising a magnetic resonance imaging-based finite element model. Dipole localisation was compared with that of the Comprehensive Epilepsy Program (CEP) evaluation. RESULTS: Using the surgical montage dipole source localisation was consistent with the CEP spike localisation for 13/14 spikes (93%, P<0.005), compared with only 5/14 spikes (36%) using the routine montage. CONCLUSIONS: Data derived from routine clinical inpatient VEM using a routine montage can yield accurate EEG dipole source localisation, but significantly more accurate localisation is obtained using the surgical montage.

Adult↗
PubMed2006

From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition.

In this work, we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pursuit algorithm and called dependency multichannel matching pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is implied by the electric leadfield. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during different physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.

Algorithms↗